Allocating partitions for executing operations of a query

ABSTRACT

A computing device is operable to receive a plurality of partition allocation requests based on execution of a corresponding plurality of query operations in conjunction with execution of a corresponding query. Processing a first partition allocation request of the plurality of partition allocation requests corresponding to execution of a first operation of the corresponding plurality of query operations is based on allocating a set of partitions of a plurality of partitions. Content is loaded into the set of partitions for access in executing the first operation. Access to the content via the set of partitions is facilitated in conjunction with execution of the first operation. The set of partitions are released based on determining the first operation has completed access of the content in conjunction with the execution of the first operation.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility patent application claims priority pursuant to 35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No. 17/647,262, entitled “RE-ORDERED PROCESSING OF READ REQUESTS”, filed Jan. 6, 2022, which is a continuation-in-part of U.S. Utility application Ser. No. 16/925,882, entitled “SINGLE PRODUCER SINGLE CONSUMER BUFFERING IN DATABASE SYSTEMS”, filed Jul. 10, 2020, issued as U.S. Pat. No. 11,249,916 on Feb. 15, 2022, which is a continuation-in-part of U.S. Utility application Ser. No. 16/267,787, entitled “TRANSFERRING DATA BETWEEN MEMORIES UTILIZING LOGICAL BLOCK ADDRESSES”, filed Feb. 5, 2019, issued as U.S. Pat. No. 10,712,967 on Jul. 14, 2020, which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No. 62/745,787, entitled “DATABASE SYSTEM AND OPERATION”, filed Oct. 15, 2018, all of which are hereby incorporated herein by reference in their entirety and made part of the present U.S. Utility patent application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networking and more particularly to database system and operation.

Description of Related Art

Computing devices are known to communicate data, process data, and/or store data. Such computing devices range from wireless smart phones, laptops, tablets, personal computers (PC), work stations, and video game devices, to data centers that support millions of web searches, stock trades, or on-line purchases every day. In general, a computing device includes a central processing unit (CPU), a memory system, user input/output interfaces, peripheral device interfaces, and an interconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using “cloud computing” to perform one or more computing functions (e.g., a service, an application, an algorithm, an arithmetic logic function, etc.) on behalf of the computer. Further, for large services, applications, and/or functions, cloud computing may be performed by multiple cloud computing resources in a distributed manner to improve the response time for completion of the service, application, and/or function.

Of the many applications a computer can perform, a database system is one of the largest and most complex applications. In general, a database system stores a large amount of data in a particular way for subsequent processing. In some situations, the hardware of the computer is a limiting factor regarding the speed at which a database system can process a particular function. In some other instances, the way in which the data is stored is a limiting factor regarding the speed of execution. In yet some other instances, restricted co-process options are a limiting factor regarding the speed of execution.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a large scale data processing network that includes a database system in accordance with the present invention;

FIG. 1A is a schematic block diagram of an embodiment of a database system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of an administrative sub-system in accordance with the present invention;

FIG. 3 is a schematic block diagram of an embodiment of a configuration sub-system in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of a parallelized data input sub-system in accordance with the present invention;

FIG. 5 is a schematic block diagram of an embodiment of a parallelized query and response (Q&R) sub-system in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a parallelized data store, retrieve, and/or process (IO & P) sub-system in accordance with the present invention;

FIG. 7 is a schematic block diagram of an embodiment of a computing device in accordance with the present invention;

FIG. 8 is a schematic block diagram of another embodiment of a computing device in accordance with the present invention;

FIG. 9 is a schematic block diagram of another embodiment of a computing device in accordance with the present invention;

FIG. 10 is a schematic block diagram of an embodiment of a node of a computing device in accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a node of a computing device in accordance with the present invention;

FIG. 12 is a schematic block diagram of an embodiment of a node of a computing device in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of a node of a computing device in accordance with the present invention;

FIG. 14 is a schematic block diagram of an embodiment of operating systems of a computing device in accordance with the present invention;

FIG. 15A is a schematic block diagram of an example of allocated memory of main memory being allocated to read data from processing core resources in accordance with the present invention;

FIG. 15B is a schematic block diagram of an example of allocated memory of main memory being allocated to store Single Producer Single Consumer (SPSC) buffers in accordance with the present invention;

FIG. 16 is a schematic block diagram of an example of allocated memory of main memory including Single Producer Single Consumer (SPSC) buffers between virtual machines of one or more processing core resources in accordance with the present invention;

FIG. 17 is a schematic block diagram of an example of data flow via operations being executed by virtual machines of one or more processing core resources in accordance with the present invention;

FIG. 18A is a logic diagram of an example of data flow of FIG. 17 between virtual machines of one or more processing core resources using the SPSC buffers in accordance with the present invention;

FIG. 18B is a schematic block diagram of an example of access to Single Producer Single Consumer (SPSC) buffers based on an operation being executed by a virtual machine of one or more processing core resources in accordance with the present invention;

FIG. 19A is a schematic block diagram of an example of linking fragments in separate physical memory spaces based on fragments of a page in logical address space in accordance with the present invention;

FIG. 19B is a logic diagram of a method for execution by a virtual machine core in accordance with the present invention;

FIG. 20 is a schematic block diagram of an example of a read operation to read data from memory space of a non-volatile memory device into an allocated buffer of main memory in accordance with the present invention;

FIG. 21A is a schematic block diagram of another example of a read operation to read data from memory space of a non-volatile memory device into an allocated buffer of main memory based on logical block addresses (LBA) in accordance with the present invention;

FIG. 21B is a logic diagram of an example of a method for creating a tagged read operation in accordance with the present invention;

FIG. 21C is a diagram of an example of a processing tagged read operations in accordance with the present invention;

FIGS. 22A and 22B are a logic diagram of an example of a method for creating tagged read operations and processing responses thereto in accordance with the present invention;

FIG. 23 is a schematic block diagram of an example of memory device (MD) buffer queues being allocated to memory devices of processing core resources of a node of a computing device in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a memory device (MD) buffer queue having separate queues for each memory device of a processing core resource of a node of a computing device and the formatting of the separate queues in accordance with the present invention;

FIG. 25 is a schematic block diagram of an example of read requests being received in an order for a memory device and information regarding the read requests being entered into memory device's queue in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of read requests being processed out of the order in which they were received, the corresponding information in the memory device queue being entered into a ring buffer as the requested are being processed, and positioned in the ring buffer based on tags in accordance with the present invention;

FIGS. 27-29A are schematic block diagrams of an example of filling up the ring buffer of FIG. 26 and outputting read data in a sequenced order in accordance with the present invention;

FIG. 29B is a logic of an example of a method for execution in accordance with the present invention;

FIG. 30 is a schematic block diagram of an example of direct memory access for a processing core resource and/or for a network connection in accordance with the present invention;

FIGS. 31-32 are schematic block diagrams of an example of processing a received data and distributed the processed table for storage in the database system when a computing device in a storage cluster is unavailable in accordance with the present invention;

FIG. 33 is a schematic block diagram of an example of allocated memory of main memory for manifest data and/or index data of a segment associated with a processing core resource in accordance with the present invention;

FIG. 34 is a schematic block diagram of an example of a partition allocator allocating partitions of the allocated memory of main memory to requesting operations in accordance with the present invention;

FIG. 35 is a logic diagram of an example of a method of allocating partitions of the allocated memory of main memory to requesting operations in accordance with the present invention; and

FIG. 36 is a schematic block diagram of another example of a partition allocator allocating partitions of the allocated memory of main memory to requesting operations in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a large-scale data processing network that includes data gathering device 1, data gathering devices 1-1 through 1-n, data system 2, data systems 2-1 through 2-N, data 3, data 3-1 through 3-n, a network 4, and a database system 10. The data systems 2-1 through 2-N provide, via the network 4, data and queries 5-1 through 5-N data to the database system 10. Alternatively, or in addition to, the data system 2 provides further data and queries directly to the database system 10. In response to the data and queries, the database system 10 issues, via the network 4, responses 6-1 through 6-N to the data systems 2-1 through 2-N. Alternatively, or in addition to, the database system 10 provides further responses directly to the data system 2. The data gathering devices 1, 1-1 through 1-n may be implemented utilizing sensors, monitors, handheld computing devices, etc. and/or a plurality of storage devices including hard drives, cloud storage, etc. The data gathering devices 1-1 through 1-n may provide real-time data to the data system 2-1 and/or any other data system and the data 3-1 through 3-n may provide stored data to the data system 2-N and/or any other data system.

FIG. 1A is a schematic block diagram of an embodiment of a database system 10 that includes data processing 7 and system administration 8. The data processing 7 includes a parallelized data input sub-system 11, a parallelized data store, retrieve, and/or process sub-system 12, a parallelized query and response sub-system 13, and system communication resources 14. The system administration 8 includes an administrative sub-system 15 and a configuration sub-system 16. The system communication resources 14 include one or more of wide area network (WAN) connections, local area network (LAN) connections, wireless connections, wireline connections, etc. to couple the sub-systems 11, 12, 13, 15, and 16 together. Each of the sub-systems 11, 12, 13, 15, and 16 include a plurality of computing devices; an example of which is discussed with reference to one or more of FIGS. 7-9 .

In an example of operation, the parallelized data input sub-system 11 receives tables of data from a data source. For example, a data set no. 1 is received when the data source includes one or more computers. As another example, the data source is a plurality of machines. As yet another example, the data source is a plurality of data mining algorithms operating on one or more computers. The data source organizes its data into a table that includes rows and columns. The columns represent fields of data for the rows. Each row corresponds to a record of data. For example, a table include payroll information for a company's employees. Each row is an employee's payroll record. The columns include data fields for employee name, address, department, annual salary, tax deduction information, direct deposit information, etc.

The parallelized data input sub-system 11 processes a table to determine how to store it. For example, the parallelized data input sub-system 11 divides the data into a plurality of data partitions. For each data partition, the parallelized data input sub-system 11 determines a number of data segments based on a desired encoding scheme. As a specific example, when a 4 of 5 encoding scheme is used (meaning any 4 of 5 encoded data elements can be used to recover the data), the parallelized data input sub-system 11 divides a data partition into 5 segments. The parallelized data input sub-system 11 then divides a data segment into data slabs. Using one or more of the columns as a key, or keys, the parallelized data input sub-system 11 sorts the data slabs. The sorted data slabs are sent, via the system communication resources 14, to the parallelized data store, retrieve, and/or process sub-system 12 for storage.

The parallelized query and response sub-system 13 receives queries regarding tables and processes the queries prior to sending them to the parallelized data store, retrieve, and/or process sub-system 12 for processing. For example, the parallelized query and response sub-system 13 receives a specific query no. 1 regarding the data set no. 1 (e.g., a specific table). The query is in a standard query format such as Open Database Connectivity (ODBC), Java Database Connectivity (JDBC), and/or SPARK. The query is assigned to a node within the sub-system 13 for subsequent processing. The assigned node identifies the relevant table, determines where and how it is stored, and determines available nodes within the parallelized data store, retrieve, and/or process sub-system 12 for processing the query.

In addition, the assigned node parses the query to create an abstract syntax tree. As a specific example, the assigned node converts an SQL (Standard Query Language) statement into a database instruction set. The assigned node then validates the abstract syntax tree. If not valid, the assigned node generates a SQL exception, determines an appropriate correction, and repeats. When the abstract syntax tree is validated, the assigned node then creates an annotated abstract syntax tree. The annotated abstract syntax tree includes the verified abstract syntax tree plus annotations regarding column names, data type(s), data aggregation or not, correlation or not, sub-query or not, and so on.

The assigned node then creates an initial query plan from the annotated abstract syntax tree. The assigned node optimizes the initial query plan using a cost analysis function (e.g., processing time, processing resources, etc.). Once the query plan is optimized, it is sent, via the system communication resources 14, to the parallelized data store, retrieve, and/or process sub-system 12 for processing.

Within the parallelized data store, retrieve, and/or process sub-system 12, a computing device is designated as a primary device for the query plan and receives it. The primary device processes the query plan to identify nodes within the parallelized data store, retrieve, and/or process sub-system 12 for processing the query plan. The primary device then sends appropriate portions of the query plan to the identified nodes for execution. The primary device receives responses from the identified nodes and processes them in accordance with the query plan. The primary device provides the resulting response to the assigned node of the parallelized query and response sub-system 13. The assigned node determines whether further processing is needed on the resulting response (e.g., joining, filtering, etc.). If not, the assigned node outputs the resulting response as the response to the query (e.g., a response for query no. 1 regarding data set no. 1). If, however, further processing is determined, the assigned node further processes the resulting response to produce the response to the query.

FIG. 2 is a schematic block diagram of an embodiment of the administrative sub-system 15 of FIG. 1A that includes one or more computing devices 18-1 through 18-n. Each of the computing devices executes an administrative processing function utilizing a corresponding administrative processing of administrative processing 19-1 through 19-n (which includes a plurality of administrative operations) that coordinates system level operations of the database system. Each computing device is coupled to an external network 17, or networks, and to the system communication resources 14 of FIG. 1A.

As will be described in greater detail with reference to one or more subsequent figures, a computing device includes a plurality of nodes and each node includes a plurality of processing core resources. Each processing core resource is capable of executing at least a portion of an administrative operation independently. This supports lock free and parallel execution of one or more administrative operations.

FIG. 3 is a schematic block diagram of an embodiment of the configuration sub-system 16 of FIG. 1A that includes one or more computing devices 18-1 through 18-n. Each of the computing devices executes a configuration processing function utilizing a corresponding configuration processing of configuration processing 20-1 through 20-n (which includes a plurality of configuration operations) that coordinates system level configurations of the database system. Each computing device is coupled to the external network 17 of FIG. 2 , or networks, and to the system communication resources 14 of FIG. 1A.

As will be described in greater detail with reference to one or more subsequent figures, a computing device includes a plurality of nodes and each node includes a plurality of processing core resources. Each processing core resource is capable of executing at least a portion of an configuration operation independently. This supports lock free and parallel execution of one or more configuration operations.

FIG. 4 is a schematic block diagram of an embodiment of the parallelized data input sub-system 11 of FIG. 1A that includes a bulk data sub-system 23 and a parallelized ingress sub-system 24. The bulk data sub-system 23 includes a plurality of computing devices 18-1 through 18-n. The computing devices of the bulk data sub-system 23 execute a bulk data processing function to retrieve a table from a network storage system 21 (e.g., a server, a cloud storage service, etc.).

The parallelized ingress sub-system 24 includes a plurality of ingress data sub-systems 25-1 through 25-p that each include a local communication resource of local communication resources 26-1 through 26-p and a plurality of computing devices 18-1 through 18-n. Each of the computing devices of the parallelized ingress sub-system 24 execute an ingress data processing function utilizing an ingress data processing of ingress data processing 28-1 through 28-n of each ingress data sub-system 25-1 through 25-p that enables the computing device to stream data of a table (e.g., a data set 30-2 as segments 29-1-1 through 29-1-n and through 29-1-p through 29-n-p) into the database system 10 of FIG. 1A via a wide area network 22A (e.g., cellular network, Internet, telephone network, etc.). The streaming may further be via corresponding local communication resources 26-1 through 26-p and via the system communication resources 14 of FIG. 1A. With the plurality of ingress data sub-systems 25-1 through 25-p, data from a plurality of tables can be streamed into the database system 10 at one time (e.g., simultaneously utilizing two or more of the ingress data sub-systems 25-1 through 25-p in a parallel fashion).

Each of the bulk data processing function and the ingress data processing function generally function as described with reference to FIG. 1 for processing a table for storage. The bulk data processing function is geared towards retrieving data of a table in a bulk fashion (e.g., a data set 30-1 as the table is stored and retrieved, via the system communication resources 14 of FIG. 1A, from storage as segments 29-1 through 29-n). The ingress data processing function, however, is geared towards receiving streaming data from one or more data sources. For example, the ingress data processing function is geared towards receiving data from a plurality of machines in a factory in a periodic or continual manner as the machines create the data.

As will be described in greater detail with reference to one or more subsequent figures, a computing device includes a plurality of nodes and each node includes a plurality of processing core resources. Each processing core resource is capable of executing at least a portion of the bulk data processing function or the ingress data processing function. In an embodiment, a plurality of processing core resources of one or more nodes executes the bulk data processing function or the ingress data processing function to produce the storage format for the data of a table.

FIG. 5 is a schematic block diagram of an embodiment of a parallelized query and results sub-system 13 that includes a plurality of computing devices 18-1 through 18-n. Each of the computing devices executes a query (Q) & response (R) function utilizing a corresponding Q & R processing of Q & R processing 33-1 through 33-n. The computing devices are coupled to the wide area network 22A of FIG. 4 to receive queries (e.g., query no. 1 regarding data set no. 1) regarding tables and to provide responses to the queries (e.g., response for query no. 1 regarding the data set no. 1). For example, the plurality of computing devices 18-1 through 18-n receives a query, via the wide area network 22, issues, via the system communication resources 14 of FIG. 1A, query components 31-1 through 31-n to the parallelized data store, retrieve, &/or process sub-system 12 of FIG. 1A, receives, via the system communication resources 14, results components 32-1 through 32-n, and issues, via the wide area network 22, a response to the query.

The Q & R function enables the computing devices to processing queries and create responses as discussed with reference to FIG. 1 . As will be described in greater detail with reference to one or more subsequent figures, a computing device includes a plurality of nodes and each node includes a plurality of processing core resources. Each processing core resource is capable of executing at least a portion of the Q & R function. In an embodiment, a plurality of processing core resources of one or more nodes executes the Q & R function to produce a response to a query.

FIG. 6 is a schematic block diagram of an embodiment of a parallelized data store, retrieve, and/or process sub-system 12 that includes a plurality of storage clusters 35-1 through 35-z. Each storage cluster includes a corresponding local communication resource of a plurality of local communication resources 26-1 through 26-z and includes a plurality of computing devices 18-1 through 18-5 and each computing device executes an input, output, and processing (IO &P) function utilizing a corresponding IO &P function of IO &P functions 34-1 through 34-5 to produce at least a portion of a resulting response. Each local communication resource may be implemented with a local communication resource of the local communication resources 26-1 through 26 p of FIG. 4 . The number of computing devices in a cluster corresponds to the number of segments in which a data partitioned is divided. For example, if a data partition is divided into five segments, a storage cluster includes five computing devices. Each computing device then stores one of the segments. As an example of operation, segments 29 are received, via the system communication resources 14 of FIG. 1A and via the local communication resources 26-1, for storage by computing device 18-4-1. Subsequent to storage, query components 31 (e.g., a query) are received, via the system communication resources 14 and the local communication resources 26-1, by the computing device 18-4-1 for processing by the IO & P data processing 34-4-1 to produce result components 32 (e.g., query response). The computing device 18-4-1 facilitates sending, via the local communication resources 26-1 and the system communication resources 14, the result components 32 to a result receiving entity.

As will be described in greater detail with reference to one or more subsequent figures, a computing device includes a plurality of nodes and each node includes a plurality of processing core resources. Each processing core resource is capable of executing at least a portion of the IO & P function. In an embodiment, a plurality of processing core resources of one or more nodes executes the IO & P function to produce at least a portion of the resulting response as discussed in FIG. 1 .

FIG. 7 is a schematic block diagram of an embodiment of a computing device 18 that includes a plurality of nodes 37-1 through 37-4 coupled to a computing device controller hub 36. The computing device controller hub 36 includes one or more of a chipset, a quick path interconnect (QPI), and an ultra path interconnection (UPI). Each node 37-1 through 37-4 includes a central processing module of central processing modules 39-1 through 39-4, a main memory of main memories 40-1 through 40-4, a disk memory of disk memories 38-1 through 38-4, and a network connection of network connections 41-1 through 41-4. In an alternate configuration, the nodes share a network connection, which is coupled to the computing device controller hub 36 or to one of the nodes as illustrated in subsequent figures.

In an embodiment, each node is capable of operating independently of the other nodes. This allows for large scale parallel operation of a query request, which significantly reduces processing time for such queries. In another embodiment, one or more node function as co-processors to share processing requirements of a particular function, or functions.

FIG. 8 is a schematic block diagram of another embodiment of a computing device is similar to the computing device of FIG. 7 with an exception that it includes a single network connection 41, which is coupled to the computing device controller hub 36. As such, each node coordinates with the computing device controller hub to transmit or receive data via the network connection.

FIG. 9 is a schematic block diagram of another embodiment of a computing device is similar to the computing device of FIG. 7 with an exception that it includes a single network connection 41, which is coupled to a central processing module of a node (e.g., to central processing module 39-1 of node 37-1). As such, each node coordinates with the central processing module via the computing device controller hub 36 to transmit or receive data via the network connection.

FIG. 10 is a schematic block diagram of an embodiment of a node 37 of computing device 18. The node 37 includes the central processing module 39, the main memory 40, the disk memory 38, and the network connection 41. The main memory 40 includes read only memory (RAM) and/or other form of volatile memory for storage of data and/or operational instructions of applications and/or of the operating system. The central processing module 39 includes a plurality of processing modules 44-1 through 44-n and an associated one or more cache memory 45. A processing module is as defined at the end of the detailed description.

The disk memory 38 includes a plurality of memory interface modules 43-1 through 43-n and a plurality of memory devices 42-1 through 42-n. The memory devices 42-1 through 42-n include, but are not limited to, solid state memory, disk drive memory, cloud storage memory, and other non-volatile memory. For each type of memory device, a different memory interface module 43-1 through 43-n is used. For example, solid state memory uses a standard, or serial, ATA (SATA), variation, or extension thereof, as its memory interface. As another example, disk drive memory devices use a small computer system interface (SCSI), variation, or extension thereof, as its memory interface.

In an embodiment, the disk memory 38 includes a plurality of solid state memory devices and corresponding memory interface modules. In another embodiment, the disk memory 38 includes a plurality of solid state memory devices, a plurality of disk memories, and corresponding memory interface modules.

The network connection 41 includes a plurality of network interface modules 46-1 through 46-n and a plurality of network cards 47-1 through 47-n. A network card includes a wireless LAN (WLAN) device (e.g., an IEEE 802.11n or another protocol), a LAN device (e.g., Ethernet), a cellular device (e.g., CDMA), etc. The corresponding network interface modules 46-1 through 46-n include a software driver for the corresponding network card and a physical connection that couples the network card to the central processing module 39 or other component(s) of the node.

The connections between the central processing module 39, the main memory 40, the disk memory 38, and the network connection 41 may be implemented in a variety of ways. For example, the connections are made through a node controller (e.g., a local version of the computing device controller hub 36). As another example, the connections are made through the computing device controller hub 36.

FIG. 11 is a schematic block diagram of an embodiment of a node 37 of a computing device 18 that is similar to the node of FIG. 10 , with a difference in the network connection. In this embodiment, the node 37 includes a single network interface module 46 and corresponding network card 47 configuration.

FIG. 12 is a schematic block diagram of an embodiment of a node 37 of a computing device 18 that is similar to the node of FIG. 10 , with a difference in the network connection. In this embodiment, the node 37 connects to a network connection via the computing device controller hub 36.

FIG. 13 is a schematic block diagram of another embodiment of a node 37 of computing device 18 that includes processing core resources 48-1 through 48-n, a memory device (MD) bus 49, a processing module (PM) bus 50, a main memory 40 and a network connection 41. The network connection 41 includes the network card 47 and the network interface module 46 of FIG. 10 . Each processing core resource includes a corresponding processing module of processing modules 44-1 through 44-n, a corresponding memory interface module of memory interface modules 43-1 through 43-n, a corresponding memory device of memory devices 42-1 through 42-n, and a corresponding cache memory of cache memories 45-1 through 45-n. In this configuration, each processing core resource can operate independently of the other processing core resources. This further supports increased parallel operation of database functions to further reduce execution time.

The main memory 40 is divided into a computing device (CD) 56 section and a database (DB) 51 section. The database section includes a database operating system (OS) area 52, a disk area 53, a network area 54, and a general area 55. The computing device section includes a computing device operating system (OS) area 57 and a general area 58. Note that each section could include more or less allocated areas for various tasks being executed by the database system.

In general, the database OS 52 allocates main memory for database operations. Once allocated, the computing device OS 57 cannot access that portion of the main memory 40. This supports lock free and independent parallel execution of one or more operations.

FIG. 14 is a schematic block diagram of an embodiment of operating systems of a computing device 18. The computing device 18 includes a computer operating system 60 and a database overriding operating system (DB OS) 61. The computer OS 60 includes process management 62, file system management 63, device management 64, memory management 66, and security 65. The processing management 62 generally includes process scheduling 67 and inter-process communication and synchronization 68. In general, the computer OS 60 is a conventional operating system used by a variety of types of computing devices. For example, the computer operating system is a personal computer operating system, a server operating system, a tablet operating system, a cell phone operating system, etc.

The database overriding operating system (DB OS) 61 includes custom DB device management 69, custom DB process management 70 (e.g., process scheduling and/or inter-process communication & synchronization), custom DB file system management 71, custom DB memory management 72, and/or custom security 73. In general, the database overriding OS 61 provides hardware components of a node for more direct access to memory, more direct access to a network connection, improved independency, improved data storage, improved data retrieval, and/or improved data processing than the computing device OS.

In an example of operation, the database overriding OS 61 controls which operating system, or portions thereof, operate with each node and/or computing device controller hub of a computing device (e.g., via OS select 75-1 through 75-n when communicating with nodes 37-1 through 37-n and via OS select 75-m when communicating with the computing device controller hub 36). For example, device management of a node is supported by the computer operating system, while process management, memory management, and file system management are supported by the database overriding operating system. To override the computer OS, the database overriding OS provides instructions to the computer OS regarding which management tasks will be controlled by the database overriding OS. The database overriding OS also provides notification to the computer OS as to which sections of the main memory it is reserving exclusively for one or more database functions, operations, and/or tasks. One or more examples of the database overriding operating system are provided in subsequent figures.

FIG. 15A is a schematic block diagram of an example of allocated memory 100 of main memory 40, as discussed with reference to FIGS. 7 and 13 , being allocated to read data 102-1 and data 102-2 from respective processing core resources 48-1 and 48-2. The processing core resources respectively includes processing modules 44-1 and 44-2, cache memories 45-1 and 45-2, memory interface modules 43-1 and 43-2, and memory devices 42-1 and 42-2 as previously discussed. The data 102-1 and data 102-2 is stored in the allocated memory 100 in pages 1-P of data blocks. For example, a page is of a selectable size (e.g., 4 KB to 2 GB). In an embodiment, a page size is selected to be 1 or 2 G bytes. When data is read from the memory device 42-1 and written into the allocated memory 100 of the main memory 40, it is desirable to have it done with efficiency in use of memory space and stored in a manner for ease of access for subsequent operations.

In this example, a portion of the DB (database) disk 53 and/or DB general 55 is allocated for storing data 102-1 and 102-2 read from the memory devices 42-1 and 42-2 of the processing core resources 48-1 and 48-2. The allocated memory 100 is of sufficient size to store a plurality of pages of data. To facilitate efficient storage and ease of use, each page is divided into fragments 1-F (e.g., 4 fragments per page or another number of fragments per page). In addition, it is desirable to avoid deadlocks with the data being stored in the allocated memory 100. To accomplish deadlock avoidance, efficiency of storage, and/or ease of use, single producer single consumer (SPSC) buffers are used between each virtual machine (VM, which is a processing core resource 48, a portion thereof, and/or multiple processing core resources).

FIG. 15B is a schematic block diagram of an example of allocated memory 100 of main memory that further stores a plurality of Single Producer Single Consumer (SPSC) buffers 104. Each SPSC buffer 104 can include one or more pointers to data stored in allocated memory 100, for example, as one or more fragments of in page. Some SPSCs may store no pointers at a given time. As discussed in further detail in conjunction with FIG. 16 , each given SPSC buffer can have a single entity assigned as a producer, where only this single producer can add pointers to the given SPSC buffer. Each given SPSC buffer can have a single entity assigned as a consumer, where only this single consumer can access and/or clear pointers stored in the given SPSC buffer.

These pointers can be generated and added in conjunction with storage of corresponding data 102 stored in pages of allocated memory. For example, pointer 105-1 is stored in SPSC 104-1 in conjunction with data 102-1 being stored in allocated memory. While not illustrated, another pointer 105-1 can be stored a different SPSC 104 in conjunction with data 102-2 being stored in allocated memory. Data 102-1 and 102-2 can then be accessed via the same or different processing core resources based on access to corresponding pointer in a corresponding SPSC buffer. Note that pointers to data 102 can only be accessed by a consumer assigned to access the corresponding SPSC buffer. Pointers to data 102 can be cleared and/or deleted by a consumer assigned to access the corresponding SPSC buffer, for example, based on having accessed the corresponding data in allocated memory, to release access of the data to other entities.

FIG. 16 is a schematic block diagram of an example of allocated memory of main memory including SPSC buffers 104-1 through 104-9 between virtual machine cores 0-2 of one or more processing core resources 48. The SPSC buffers 104-1-104-9 of FIG. 16 can be stored in allocated memory 100 and/or in another portion of main memory 40, for example, as illustrated in FIG. 15B. The SPSC buffers 104-1-104-9 of FIG. 16 can implement the SPSC buffers of FIG. 15B.

A given processing core resource 48 can implement a single, corresponding virtual machine cores and/or can implement multiple corresponding virtual machine core. Each virtual machine cores can perform some or all of their functionality as described herein by utilizing processing and/or memory resources of the corresponding processing core resources. For example, virtual machine cores can perform some or all of their functionality by on utilizing the processing module 44, cache memory 45, memory device 42, and/or memory interface module 43 of the corresponding processing core resource.

An SPSC buffer is a one-way buffer, meaning the producer puts data in the SPSC buffer and only the consumer can take that data out of the buffer. As shown, there are two SPSC buffers between each virtual machine core: one in each direction. In addition, each virtual machine (VM) core has its own SPSC buffer, where the VM core is the producer and the consumer. The arrows indicated denote the direction of each SPSC buffer: an arrow from a VM core pointing to a particular SPSC buffer 104 denotes that VM core is the single producer of the particular SPSC buffer 104, and an arrow from a particular SPSC buffer 104 to a VM core denotes that VM core is the single consumer of the particular SPSC buffer 104. In this example, VM core 0 is assigned as the producer and the consumer of SPSC 104-1; VM core 1 is assigned as the producer and the consumer of SPSC 104-2; VM core 2 is assigned as the producer and the consumer of SPSC 104-3; VM core 0 is assigned as the producer of SPSC 104-4 and VM core 1 is assigned as the consumer of SPSC 104-4; VM core 1 is assigned as the producer of SPSC 104-5 and VM core 0 is assigned as the consumer of SPSC 104-5; VM core 1 is assigned as the producer of SPSC 104-6 and VM core 2 is assigned as the consumer of SPSC 104-6; VM core 2 is assigned as the producer of SPSC 104-7 and VM core 1 is assigned as the consumer of SPSC 104-7; VM core 0 is assigned as the producer of SPSC 104-8 and VM core 2 is assigned as the consumer of SPSC 104-8; and VM core 2 is assigned as the producer of SPSC 104-9 and VM core 0 is assigned as the consumer of SPSC 104-9.

Because exactly one SPSC buffers is maintained for every possible producer/consumer pair of the set of VM cores, including producer/consumer pairs that include the same VM core, the number of SPSC buffers is equal to the square of the number of VM cores. In this example, nine SPSC buffers are therefore maintained for the three VM cores. In other embodiments with any number of VM cores in the set of VM cores, the number of SPSC buffers can similarly be equal to the square of the number of VM cores to similarly implement exactly one SPSC buffer for every possible producer/consumer pair of any set of VM cores.

The VM cores uses the SPSC buffers to store pointers to the data, not the data itself such that the SPSC buffers are very small in comparison to the data they reference. Use of the SPSC buffers allows the VM cores to execute multiple threads that access the same data and/or permutations of the data.

Various intermediate data that is generated from previous intermediate data as a sequence of operations are performed can each be stored in the allocated memory with corresponding pointers stored in SPSC buffers. For example, a pointer to intermediate data is stored in exactly one SPSC buffer for access by exactly one VM core.

In addition, the VM cores use the same contract terms of a common contract to help avoid a deadlock. The contract terms of the common contract can include (a) once a VM places data in allocated memory of the DB memory space of the main memory and/or places information in an SPSC buffer, it cannot access that data until it is released by a consumer; and (b) it won't place data in the allocated memory and/or an SPSC unless it knows it can advance the operational sequence of a query. This can be based on each VM core's knowledge of the data flow for the query, such as the data flow illustrated in FIG. 17 .

Adhering to contract term (a) of the common contract can include a virtual machine core not accessing data during a temporal period after writing the intermediate data to allocated memory and after writing the corresponding pointer to a given SPSC buffer based on determining the corresponding pointer has not been cleared from the a given SPSC buffer by a single consumer of the buffer during the temporal period.

Contract term (b) of the common contract can correspond to an operational sequence advancement rule, where a VM core determines whether the operational sequence advancement rule is met, and where a VM core only places data in the allocated memory and/or places a pointer in an SPSC buffer based on determining it can advance the operational sequence of a query. For example, the VM core determines places data in the allocated memory and/or places a pointer in an SPSC buffer will advance the operational sequence of a query based on determining whether consumer VM core of the SPSC buffer can independently operate upon the data and/or make progress upon the data. Adhering to contract term (b) can include only placing data in the allocated memory and placing a corresponding pointer in a given SPSC buffer when the operational sequence advancement rule is determined to be met. For example, this is based on the VM core resource determining which VM core performs a next operation on the intermediate data, and storing the corresponding pointer only in the SPSC buffer that is access by this determined VM core.

As a particular example, a given VM core has knowledge of some or all of the data flow of a given query. As another particular example, a given VM core has knowledge of a given set of operations it is responsible for performing, and further has knowledge of which VM core requires use of any intermediate data resulting from performance of each of the given set of operations. A given VM core ensures placement of a pointer in an SPSC buffer in accordance with the operational sequence advancement rule by identifying which VM core requires use of the data next in accordance with the data flow; by identifying which SPSC buffer has the given VM core assigned the producer and this identified VM core as the consumer; and by adding a pointer to this data's location in allocated memory in the identified SPSC buffer, for example, based on having written this data to the allocated memory.

In some cases, the operational sequence advancement rule of the common contract can correspond to an operational sequence advancement rule can further dictate that a VM core cannot take ownership of data in main memory unless it can independently operate upon the data and/or make progress upon the data itself. Adhering to the operational sequence advancement rule can include determines whether the VM core itself can independently operate upon data and/or make progress upon data prior to its accessing of the data in memory and/or prior to its performing operations upon the data.

In some cases, as the various intermediate data is generated, it can replace and/or be written over prior intermediate data generated in a prior operation, for example, where given data is modified over time to render a final result rather than being copied in multiple locations. For example, when second intermediate data for a given data flow and/or a given query is generated by performing an operation on first intermediate data, the second intermediate data overwrites the first intermediate data. In such cases, the pointer for the second intermediate data can point to a same memory location as the first intermediate data and/or can correspond to a same pointer. In such cases, a pointer to this common memory location data is stored in exactly one SPSC buffer for access by exactly one VM core at a given time, in accordance with the operations being sequentially performed in order.

In other cases, as the various intermediate data is generated, it can be written in different locations of the allocated memory than the prior intermediate data. First intermediate data utilized to generate second intermediate data can be stored in a different location from the first intermediate data to enable the first intermediate data to remain accessible for use by other VM cores. For example, the first intermediate data is released by a given, first VM core after use, based on the given VM core being a consumer of a given SPSC buffer than includes a pointer to the first intermediate data, having generated second intermediate data from the first intermediate data, and having cleared the pointer to the first intermediate data from the given SPSC buffer. Another, second VM core, such as a VM core that generated the first intermediate data and added the pointer to the first intermediate data to the given SPSC buffer as a producer of the given SPSC buffer, can access the first intermediate data for other purposes based on the pointer to the first intermediate data being cleared the given SPSC buffer by the first VM core.

In some cases, the various intermediate data generated by VM cores can be stored in pages of allocated memory. For example, first intermediate data can be stored as one or more fragments in one page. Second intermediate data generated by accessing the first intermediate data via access to pointer by a consumer VM core of a corresponding SPSC buffer can be stored by this consumer VM core as one or more fragments in the same or different page. Intermediate data that includes multiple fragments can have the multiple fragments linked via linking information indicated in the header of one or more of the multiple fragments as discussed in conjunction with FIG. 19 .

FIG. 17 is a schematic block diagram of an example of data flow for a query 106 via operations being executed by virtual machines 0-2 of one or more processing core resources. In this example, VM core 0 is responsible for executing operation 0 (op 0), op 1, and op 2; VM core 1 is responsible for executing op 3, op 4, and op 5; and VM core 2 is response for executing op 6, op 7, and op 8. For this example, the operation may be any of the operations of the database instruction set and the suffix number is used to indicate that the operations are separate operations. Operations 0, 2, 5, 7, and 8 are related for a query and represent data flow for execution of these operations for the given data flow for a query 106. Operations 1, 3, 4, and 6 can be other operations of the query 106 that are independent from the operations 0, 2, 5, 7, and 8, for example, based on not requiring use of data outputted by those operations and/or based on not having output utilized as input for those operation. Alternatively, 1, 3, 4, and 6 can be independent from operations 0, 2, 5, 7, and 8 based on being operations of one or more other queries being concurrently executed by VM cores 0, 1, and 2.

FIG. 18A is a logic diagram of an example of data flow of FIG. 17 between virtual machines of one or more processing core resources using the SPSC buffers. As shown in FIG. 17 , the operational flow of data is from op 0 to op 2, to op 5, to op 7, and then to op 8. Starting with op 0 of the left flow diagram, assume that it is a read request to read data from a memory device. The VM core 0, which is executing op 0 as illustrated in FIG. 17 , performs the operation of reading the requested data from the memory device, such as memory device 42 of the corresponding processing core resource 48, and placing it into the allocated memory 100 of the main memory 40 as discussed in conjunction with FIGS. 15A and 15B. In addition, as a producer, it adds a pointer into its own SPCS buffer 104-1 of FIG. 16 with VM core 0 as both the producer and the consumer based on determining it also performs the next operation in the sequence of FIG. 17 .

As the consumer, VM core 0 accesses the SPSC buffer 104-1 to retrieve the pointer for the data stored in the allocated memory of the main memory. VM core 0 then accesses the data from the allocated memory and performs op 2 on the data to produce a first intermediate data (ID). The VM core 0 then writes the first ID into the allocated memory of the main memory. As a producer, VM core 0 writes a pointer to the first ID on the allocated memory into SPSC 104-4 of FIG. 16 with VM core 0 as the producer and VM core 1 as the consumer based on determining VM core 1 is responsible for the next operation in the sequence of FIG. 17 (e.g., op 5).

Next, the VM core 1 performs operation 5. These steps of performing operation 5 by virtual machine core 1 are illustrated in FIG. 18B, where the first ID corresponds to ID second ID corresponds to ID 2. As the consumer, VM core 1 accesses the SPSC buffer 104-4 to retrieve the pointer for the first ID stored in the allocated memory of the main memory. VM core 1 then accesses the first ID from the allocated memory and performs op 5 on the data to produce a second intermediate data (ID). The VM core 1 then writes the second ID into the allocated memory of the main memory. For example, the second ID is written to the same portion of the allocated memory as the first ID, where writing the second ID includes overwriting and/or replacing the first ID in memory. In other cases, the second ID is written to a different portion of the allocated memory from the first ID.

The VM core 1 can optionally clear and/or otherwise remove the pointer from the SPSC buffer 104-4 based on having generated the second ID and having completed its use of the first ID. For example, the VM core 0 and/or another VM core can again access the intermediate data 1 based on the clearing of the pointer from the SPSC buffer 104-4 based on the contract term (b) of the common contract.

As a producer, VM core 1 writes a pointer to the second ID on the allocated memory into the SPSC 104-6 of FIG. 16 with VM core 1 as the producer and VM core 2 as the consumer based on determining VM core 2 is responsible for the next operation in the sequence of FIG. 17 (e.g., op 7). In cases where the second ID is written to the same portion of the allocated memory as the first ID, this pointer can be the same as the pointer retrieved from SPSC buffer 104-4. In cases where the second ID is written to a different portion of the allocated memory as the first ID, this pointer can be different from the pointer retrieved from SPSC buffer 104-4.

As the consumer, VM core 2 accesses the SPSC buffer 104-6 to retrieve the pointer for the second ID stored in the allocated memory of the main memory. VM core 2 then accesses the second ID from the allocated memory and performs op 7 on the data to produce further data, such as final data, for this operation sequence. The VM core 2 then writes this data into the allocated memory of the main memory. As a producer, VM core 2 writes a pointer to the final data on the allocated memory into SPSC 104-3 of FIG. 16 with VM core 2 as both the producer and the consumer based on determining it also performs the next operation in the sequence of FIG. 17 (e.g. op 8). In other cases, if another VM core is responsible for outputting this final data, the VM core 2 writes a pointer to the final data on the allocated memory into another SPSC 104 of FIG. 16 with VM core 2 as the producer and this other VM core as the consumer.

In cases where op 8 is to be performed by VM core 2 as illustrated in FIG. 17 , Alternatively, VM core 2 performs op 8 to output the final data, for example, without updating an SPSC buffer based on the final data being outputted. This can include VM core 2 accessing the SPSC buffer 104-3 to retrieve the pointer for final data stored in the allocated memory of the main memory. VM core 2 then accesses the final data from the allocated memory and performs op 8 on the data to output the corresponding final data.

Note that in some cases, at a given time, an SPSC buffer 104 may include multiple pointers, for example corresponding to intermediate data generated in conjunction with execution of multiple queries concurrently. In some cases, based on the order in which various operations of various queries are performed by respective VM cores, some SPSCs may include only one pointer at particular points in time, may include no pointers at particular points in time, and/or may include multiple pointers for intermediate data of multiple different queries at particular points in time. In some cases, some SPSCs may include multiple pointers for multiple intermediate data of a same query at a particular point in time when the corresponding operations to be performed on the multiple intermediate data can be performed independently and/or in parallel. In some cases, a SPSCs will never include multiple pointers for multiple intermediate data of a same query at a particular point in time when the corresponding operations to be performed on the multiple intermediate data are to be performed serially and/or otherwise have data dependency.

For example, consider the case where another query being performed by VM cores 0, 1, and 2 includes performance of, in order, operations 1, 3, 4, and 6 of FIG. 17 . At some point in time, intermediate data generated by VM core 0 based on performing operation 1 will be stored in allocated memory with a corresponding pointer placed by VM core 0 in SPSC 104-4 based on VM core 0 being the producer of SPSC 104-4, based on the corresponding intermediate data being next used by VM core 1 in accordance with the flow for this other query, and based on VM core 1 being the consumer of SPSC 104-4. In particular, at a given time, SPSC 104-4 may store a pointer to intermediate data generated by VM core 0 via performance of operation 1, and may also store the pointer to intermediate data generated by VM core 0 via performance of operation 2 as discussed previously. Similarly, at a given time, SPSC 104-6 may store a pointer to intermediate data generated by VM core 1 via performance of operation 4 based on operation 6 of this other query being performed next by VM core 2. At this given time, may also store the pointer to the intermediate data generated by VM core 1 via performance of operation 5 as discussed previously.

FIG. 18B illustrates a particular example illustrating the execution of operation 5 of FIGS. 17 and 18A by VM core 1. As the consumer, VM core 1 accesses the SPSC buffer 104-4 to retrieve a pointer 1 for intermediate data (ID) 1 stored in the allocated memory 100. VM core 1 then accesses ID 1 from the allocated memory and performs op 5 on the data to produce intermediate data 2. The VM core 1 then writes the ID 2 into the allocated memory of the main memory. As a producer, VM core 1 writes a pointer 2 to the ID 2 on the allocated memory into the SPSC 104-6 with VM core 1 as the producer.

In various embodiments, a virtual machine core, such as a virtual machine core of a processing core resource 48, includes and/or accesses at least one processor and a memory that stores operational instructions. The virtual machine core can be implemented as one of the virtual machine cores of FIGS. 16, 17, 18A, and/or 18B. The processing core resource 48 can be implemented as one of the processing core resources 48 of FIGS. 15A and/or 15B, and/or any other embodiment of processing core resource 48 discussed herein. The operational instructions, when executed by the at least one processor, cause the virtual machine core to: retrieve a first pointer by accessing a first buffer of a plurality of buffers stored in allocated memory of a main memory based on assignment as a single consumer of the first buffer; access first intermediate data in the allocated memory by utilizing the first pointer; generate second intermediate data by executing one of an ordered set of operations on the first intermediate data; write the second intermediate data to the allocated memory; and/or write a second pointer to a second buffer of the plurality of buffers based on assignment as a single producer of the second buffer. The operational instructions, when executed by the at least one processor, can cause the virtual machine core to perform some or all of the steps and/or additional functionality discussed in conjunction with FIG. 19B.

FIG. 19A is a schematic block diagram of an example of linking fragments in separate physical memory addresses 110 (spaces) based on fragments of a page in logical addresses 108 (spaces). In this example, the fragments of a page (0-z) are sequential in logical address space. In physical address space, however, the fragments are not sequential and very often not contiguous.

Each fragment includes a header section 0-1 or 3-4 that includes a count of the number of whole data values in the fragment and information as to whether it is linked to one or more other fragments. Fragments are linked together for temporary storage in allocated memory of the DB memory space of the main memory when a data value spans two fragments. The size of data values ranges from a byte to 1 M Byte or more.

In the example, data value “2” spans the first and second fragments (e.g., as depicted with headers 1 and 2). Accordingly, the fragments 1 and 2 are linked together when a page, or a relevant portion thereof, is to be written to the allocated memory. With fragments 1 and 2 linked together, when they are written into the allocated memory, they will be contiguous (e.g., as depicted with headers 3 and 4). Thus, data value “2” is contiguous in the allocated memory.

In some embodiments, multiple fragments of intermediate data generated by a virtual machine core as discussed in conjunction with FIG. 17 can be linked together in a page written to allocated memory. In such embodiments, multiple fragments of intermediate data generated by a virtual machine core as discussed in conjunction with FIG. 17 can be linked together based on this virtual machine core generating the header of the header section of one or more fragments to indicate the linking information as illustrated in FIG. 19A, and storing the multiple linked fragments in allocated memory accordingly as the intermediate and/or final data stored by the virtual machine core. The corresponding pointer can point to a first fragment, such as one of the multiple fragments that includes the linking information in the header section.

When the same or different virtual machine core accesses this intermediate data in conjunction with performing a next operation as discussed in conjunction with FIG. 17 , the virtual machine core can access the corresponding pointer in the corresponding SPSC buffer as discussed previously, and can utilize the corresponding pointer to access the first fragment. This same or different virtual machine core can extract the linking information from the header section to determine that additional fragments are included in the corresponding intermediate data, and the virtual machine core can also access the denoted additional fragments indicated in the linking information as being linked to the first fragment. This same or different virtual machine core can then perform its operation upon the intermediate data included in the multiple linked fragments to generate subsequent intermediate data and/or final data.

FIG. 19B is a flow diagram illustrating a method for execution by a virtual machine core of a processing core resource 48, such as a virtual machine core of FIGS. 16, 17, 18A, and/or 18B implemented by a processing core resource 48 of FIGS. 15A and/or 15B. In some cases, multiple virtual machine core can each execute some or all of the steps of FIG. 19B in conjunction with execution of their respective operations, for example, as illustrated and discussed in conjunction with FIGS. 17, 18A, and/or 18B. The method of FIG. 19B can include performance of some or all steps of the method of FIG. 18A by one or more virtual machine cores. Some or all steps of FIG. 19B can be performed by any processing module of the database system 10.

Step 1902 includes retrieving a first pointer by accessing a first buffer of a plurality of buffers. The plurality of buffers can be stored in allocated memory of a main memory based on assignment of the virtual machine core as a single consumer of the first buffer. For example, each of the plurality of buffers is implemented as an SPSC buffer 104 of FIGS. 15B and/or 16 . The first buffer can optionally be stored in any other memory accessible by the virtual machine core.

Step 1904 includes accessing first intermediate data in the allocated memory by utilizing the first pointer. The first pointer can denote the location of the first intermediate data in the allocated memory. Step 1906 includes generating second intermediate data by executing one of an ordered set of operations on the first intermediate data. For example, the ordered set of operations can correspond to a data flow of operations, such as the data flow of query 106. In particular, the query 106 includes an ordered set of operations including, in order, operation 0, 2, 5, 7, and 8. In some cases, the accessing of the first pointer and the first intermediate data is based on the ordered operation requiring the first intermediate data.

Step 1908 includes writing the second intermediate data to the allocated memory. Step 1910 includes writing a second pointer to a second buffer of the plurality of buffers based on assignment based on assignment of the virtual machine core as a single producer of the second buffer. The second pointer can denote the location of the second intermediate data in the allocated memory.

In various embodiments, the virtual machine core is included in a plurality of virtual machine cores of one or more processing core resources 48, such as the set of virtual machine cores 0, 1, and 2 of FIG. 16 . Pointers are written to each given buffer of the plurality of buffers by exactly one corresponding virtual machine core of the plurality of virtual machine cores assigned as a single producer of each given buffer. Pointers are retrieved from each buffer of the plurality of buffers by exactly one corresponding virtual machine core of the plurality of virtual machine cores assigned as a single consumer of each given buffer.

In various embodiments, each single producers of each of a proper subset of the plurality of buffers are assigned as the same one of the plurality of virtual machine cores as each single consumer of the each of a proper subset of the plurality of buffers. For example, the SPSC buffers 104-1, 104-2, and 104-3 constitute such a proper subset of the set of SPSC buffers 104-1-104-9. In various embodiments, the plurality of buffers includes a number of buffers equal to a squaring of a number of virtual machine cores in the plurality of virtual machine cores, for example, based on the plurality of buffers including the including a number of buffers in the proper subset equal to the number of number of virtual machine cores in the plurality of virtual machine cores, and further including another set of buffers corresponding to every possible pair of different virtual machine cores of the plurality of virtual machine cores.

In various embodiments, the method further includes retrieving the second pointer by accessing the second buffer of a plurality of buffers stored in allocated memory of a main memory based on assignment as a single consumer of the second buffer. The method can further include accessing the second intermediate data in the allocated memory by utilizing the first pointer. The method can further include generating third intermediate data by executing another one of the ordered set of operations on the second intermediate data, wherein the another one of the ordered set of operations is sequentially after the one of the ordered set of operations in accordance with an ordering of the ordered set of operations.

In various embodiments, the method further includes generating the first intermediate data. The method can further include writing the first intermediate data to the allocated memory. The method can further include writing the first pointer to the first buffer based on assignment as a single producer of the first buffer. In various embodiments, the first intermediate data is generated by executing another one of an ordered set of operations on other data, where the another one of the ordered set of operators is sequentially prior to the one of the ordered set of operations in accordance with an ordering of the ordered set of operations. In various embodiments, the method further includes reading the other data from a memory device that is distinct from the allocated memory, such as a disk drive storing the other data, where the virtual machine core reads the other data to the main memory in performing one of the ordered set of operations, such as a first operation in the ordering. The method can further include writing the other data to the allocated memory, writing another pointer to the first buffer of the plurality of buffers based on assignment as the single producer of the first buffer, and/or accessing the other data from the allocated memory by utilizing the first pointer.

In various embodiments, the virtual machine core is included in a plurality of virtual machine cores, and a second one of the plurality of virtual machine cores is assigned as a single consumer of the second buffer. The second one of the plurality of virtual machine cores can perform operations, and can optionally perform some or all same or similar steps of FIG. 19B. These operations performed by the second one of the plurality of virtual machine cores can include retrieving the second pointer by accessing the second buffer based on assignment as the single consumer of the second buffer, retrieving the second intermediate data in the allocated memory by utilizing the second pointer, and/or generating third intermediate data by executing another one of the ordered set of operations on the second intermediate data.

In various embodiments, a third one of the plurality of virtual machine cores is assigned as a single producer of the first buffer. The third one of the plurality of virtual machine cores can perform operations, and can optionally perform some or all same or similar steps of FIG. 19B. These operations performed by the third one of the plurality of virtual machine cores can include generating the first intermediate data, writing the first intermediate data to the allocated memory, and/or and writing the first pointer to the first buffer based on assignment as a single producer of the first buffer.

In various embodiments, the method includes executing one proper subset of a plurality of proper subsets of the ordered set of operations in accordance with a common contract, such as the contract discussed in conjunction with FIG. 16 . The one proper subset can include consecutive ones of the ordered set of operations that includes the one of the ordered set of operations. Other ones of the plurality of virtual machine cores each execute a corresponding other proper subset of the plurality of proper subsets of the ordered set of operations in accordance with the common contract, and execution of the ordered set of operations by the plurality of virtual machine cores renders execution of a corresponding query. In various embodiments, each of the plurality of virtual machine cores execute the corresponding other proper subset of the plurality of proper subsets of the ordered set of operations by accessing at least one of the plurality of buffer to which the each of the plurality of virtual machine cores is assigned as a single consumer.

For example, these proper subsets can be implemented as illustrated in FIG. 17 , where the ordered set of operations includes operations 0, 2, 5, 7, and 8, where virtual machine core 0 executes a first proper subset of consecutive operations that includes operations 0 and 2, where virtual machine core 1 executes a second proper subset of consecutive operations that includes operation 5, and where virtual machine core 2 executes a third proper subset of consecutive operations that includes operations 7 and 8. Execution of operations 0, 2, 5, 7, and 8 by virtual machine cores 0, 1, and 2 renders execution of the corresponding query 106.

In various embodiments, the method further includes determining one of the plurality of virtual machine cores responsible for executing a next operation in the ordered set of operations that is sequentially after the one of the ordered set of operations in accordance with an ordering of the ordered set of operations. The second pointer is written to the second buffer of the plurality of buffers further based on the one of the plurality of virtual machine cores being assigned as a single consumer of the second buffer.

In various embodiments, the method further includes clearing the first pointer from the first buffer based on utilizing the first pointer to access the first intermediate data in the allocated memory. In various embodiments, the second intermediate data is written to the allocated memory based on a determining an operational sequence advancement rule of a common contract is met. In various embodiments, the second intermediate data is not accessed by the virtual machine core during a temporal period after writing the second intermediate data to the allocated memory based on determining the second pointer has not been cleared from the second buffer by a single consumer of the second buffer during the temporal period, for example, in accordance with the common contract.

In various embodiments, writing the second intermediate data includes generating header data for at least one data fragment of the second intermediate data that includes fragment linking data that identifies at least one additional data fragment of the second intermediate data, and includes storing the at least one data fragment and the at least one additional data fragment in non-consecutive physical addresses of the main memory. For example, the second intermediate data is written, stored, and/or accessed in accordance with linked fragments as discussed in conjunction with FIG. 19 .

In various embodiments, accessing the first intermediate data includes accessing at least one data fragment of the first intermediate data, identifying at least one additional data fragment of the first intermediate data by utilizing fragment linking data in header data of the at least one data fragment, and/or accessing the at least one additional data fragment of the first intermediate data based on the fragment linking data. For example, this at least one data fragment and the at least one additional data fragment are stored in non-consecutive physical addresses of the main memory. For example, the first intermediate data is written, stored, and/or accessed in accordance with linked fragments as discussed in conjunction with FIG. 19 .

In various embodiments, a non-transitory computer readable storage medium includes at least one memory section that stores operational instructions. The operational instructions, when executed by a processing module that includes a processor and a memory, causes the processing module to: retrieve a first pointer by accessing a first buffer of a plurality of buffers stored in allocated memory of a main memory based on assignment as a single consumer of the first buffer; access first intermediate data in the allocated memory by utilizing the first pointer; generate second intermediate data by executing one of an ordered set of operations on the first intermediate data; write the second intermediate data to the allocated memory; and/or write a second pointer to a second buffer of the plurality of buffers based on assignment as a single producer of the second buffer.

FIG. 20 is a schematic block diagram of an example of a processing core resource 48 executing a read operation to read data from memory space 116 of a (non-volatile) memory device 42 into an ordered buffer 112 of main memory 40. The processing core resource 48 includes a processing module 44, cache memory 45, a memory interface module 43, and memory device(s) 42 as previously discussed. The memory device 42 stores data in a memory space 116 in data blocks. Each data block is of a fixed size (e.g., logical blocks having a size of 4 K Bytes). When data is read from the memory device 42 and subsequently written into the ordered buffer 112 of the main memory 40, it is desirable to so with as minimal amount of reads as possible and to maintain the order of the data in the ordered buffer 112.

In an example, data of interest is stored as data blocks 0-Z, which may be data from a segment of a segment group of a partition of a table in the memory device(s) 42. In general, the data blocks are stored in an order; block 0 being the first and block Z being the last. When read operations for the data blocks are made, they are made in order; read operation for block 0 is first and read operation for block Z is last. The read operations are sent to the non-volatile memory in the order created, however, the non-volatile memory does not respond to the read operations in the order sent due to the general operations of non-volatile memories.

The ordering of the data blocks is important for processing of them (i.e., consumption of the data block). As such, it is desirable to store the data blocks in the buffer of main memory in the desired order and not in the order the non-volatile memory responded to the read operations.

FIG. 21A is a schematic block diagram of another example of a processing entity (e.g., one or more processing core resources of a computing device, one or more nodes of the computing device, one or more processing core resources of another computing device, and/or one or more nodes of the other computing device) executing a read operation to read data from non-volatile memory device (e.g., memory space 116) for data units 0-5. Data units 0-5, which are generally not of a fixed size, are stored in logic blocks LBAi, LBAi+1, LBAi+2, LBAi+3, which are of a fixed size. Read operations are created to read data units 0-5, but on a logic block level.

For example, a read operation is created for logic block LBAi, which contains all of data units 0-2 and part of data unit 3. While creating the read operation for LBAi, the processing entity also creates a unique tag value for the read operation and creates a counter value. The unique tag value uniquely identifies LBAi for this read operation and is used to identify the response from the non-volatile memory. The counter value reflects the number of data units that are fully contained in the data block and that are partially contained in the data block. For this example, LBAi has three full data units (0-2) and one partial data unit (3), thus the counter value is 4.

The processing entity also creates read operations for logic blocks LBAi+1, LBAi+2, LBAi+3, which includes corresponding unique tag values and counter values. For example, the processing entity creates a read operation for logic block LBAi+1, which includes unique tag ID (tag i+1) and a counter value of 3 for the data units (3-5) at least partially contained in the logic block. As another example, the processing entity creates a read operation for logic block LBAi+2, which includes unique tag ID (tag i+2) and a counter value of 1 for data unit 5, which spans the entire logic block. As yet another example, the processing entity creates a read operation for logic block LBAi+3, which includes unique tag ID (tag i+3) and a counter value of 1 for data unit 5, which spans a portion of the logic block. The processing entity sends the read operations and their corresponding tags to the non-volatile memory.

FIG. 21B is a logic diagram of an example of a method for creating a tagged read operation by a processing entity. The method begins at step 250 where the processing entity identifies a data unit that is to be read from non-volatile memory. The method continues at step 252 where the processing entity determines whether a read operation exists for the logic block of the non-volatile memory in which the data unit is stored. If yes, the method continues at step 254 where the processing entity increments the counter value for the logic block. The method then repeats for the next data unit to be read or ends when all data units that are to be read have been processed in this manner.

When a read operation does not exist for the data unit, the method continues at step 256 where the processing entity creates a read operation for the logic block and creates a unique tag value for the logic block. The method continues to step 258 where the processing entity creates a counter value for the logic block and sets it to 1 (for the data unit). The method then repeats for the next data unit to be read or ends when all data units that are to be read have been processed in this manner.

FIG. 21C is a diagram of an example of processing tagged read operations of FIG. 21A by a processing entity. As discussed above, the processing entity sends the tagged read operations in the order corresponding to the order of the logic blocks: LBAi read operation first, LBAi+1 read operation second, and so on. The non-volatile memory, however, does not typically process read operations in the order they were sent, but in a more random order. For this example, the non-volatile memory responded to the read operation for LBAi+2 first, then to the read operation for LBAi, then to the read operation for LBAi+3, and finally to the read operation for LBAi+1.

After sending the read operations to the non-volatile memory, the processing entity sets a flag for the next expected tag. The next expected tag corresponds to the next logic block in the order of logic blocks that have been received. In the first column of the example, the next expected tag is set to “i”, which is the tag for the read operation for logic block LBAi (the first logic block in the order).

The non-volatile memory, however, provides a read response i+2 (which includes tag i+2) to the read operation for logic block BLAi+2. In this instance, the process entity keeps the next expected tag set to “i”, since it has not yet received the response to the read operation for logic block LBAi. Since the current tag is not equal to the next expected tag, the processing entity writes the data unit(s) of the current data block (e.g., LBAi+2) into LBAi+2 position of a virtual machine (VM) buffer (i.e., the ordered buffer 112 of FIG. 20 ). In addition, the processing entity queues the tag i+2. Note that data units of LBAi+2 are not made available for consumption at this time.

The next response from the non-volatile memory is read response i (with tag i) for the read operation for logic block LBAi. In this instance, the read response tag matches the next expected tag of i. As such, the processing entity writes the content of read response i (i.e., the data unit(s) stored in LBAi) into position LBAi of the VM buffer and makes the whole data units available of consumption. The processing entity adjusts the next expected tag to i+1 and checks to see if the next expected tag has been queued. In this case, it hasn't. Note that a partial data unit of a logic block is not made available for consumption until it is fully stored in order in the VM buffer. Further note that the data units of LBAi+2 are still not available for consumption.

The non-volatile memory next provides read response i+3 (with tag i+3) for read operation for logic block LBAi+3. Since the next expected tag is i+1, the tags do not match. Thus, the processing entity stores the content of the read response for the LBAi+3 in the LBAi+3 position of the VM buffer, but does not make the content (i.e., the data unit, or units) available for consumption. In addition, the processing entity queues the tag i+3. During this time, data units stored in the LBAi section of the VM buffer may have been consumed (e.g., retrieved for processing). If so, the counter value is decremented by the number of data units that have been consumed. When the counter value reaches zero, the logic block position of the VM buffer is released.

This example continues with the non-volatile memory providing read response i+1 (with tag i+1) to read operation LBAi+1. Since this tag matches the next expected tag, the processing entity stores the content read response i+1 in LBAi+1 position of the VM buffer and makes the content (e.g., the hole data units of LBAi) available for consumption. The processing entity then updates the next expected tag to i+2 and checks the queue for i+2. Since the queue includes i+2, the processing entity makes the contents of LBAi+2 available for consumption, updates the next expected tag to i+3, and checks the queue.

Since the queue includes i+3, the processing entity makes the contents of LBAi+3 available for consumption. At this point, all of the data units are available for consumption. As the data units are consumed from the logic blocks, the counters of the logic blocks are decremented. When a logic block counter reaches zero, the logic block location in the VM buffer is released. This allows for ordering to be maintained despite out of order responses by the non-volatile memory, which increases efficiency and parallelism of processing data for a query.

FIGS. 22A and 22B are a logic diagram of an example of a method for creating tagged read operations and processing responses thereto by a processing entity. The method begins at step 260 of FIG. 22A where the processing entity identifies data units to read from non-volatile memory and to write them into ordered buffers of volatile memory. The volatile memory includes random access memory and the non-volatile memory including one or more of a solid-state memory device and a disk memory device. The data units have a variety of data sizes and are stored in “n” number of logical data blocks of the non-volatile memory, wherein “n” is an integer greater than or equal to two. In this example, at least one data unit is stored in two or more logical data blocks (e.g., data unit 3 of FIG. 21A). Also in this example, the logical data blocks storing the data units are contiguous (e.g., have logical addresses that are contiguous), yet the physical memory locations of logic blocks in the disk memory are not contiguous.

In one example, the processing entity identifies the data units by receiving an operation that includes reading the data units from the disk memory and writing the plurality of data units into the ordered buffer. In another example, the processing entity accessing metadata regarding the plurality of data units to read to determine the logic blocks to read from the disk memory. The processing entity uses the number of logic blocks to read to create an ordered buffer in the volatile main memory. Note that, in an embodiment, creating the ordered buffer is done in accordance with a process specific operating system of the computing device and that the process specific operating system overrides, with respect to the volatile main memory, a general operating system of the computing device.

The method continues at step 262 where the processing entity generates “n” number of read operations regarding the plurality of data units (i.e., one for each logic block to be read). In addition, the processing entity determines a unique data unit count value (e.g., counter value) for each read operation. The unique data unit count value indicates a number of data units that are at least partially stored within a corresponding logical data block (e.g., logic block). The counter value is used to determine when the logic block in the volatile main memory can be released. For instance, the processing entity tracks when a data unit of a logic block of the volatile main memory is consumed. When a data unit is consumed, the counter value is decremented. When the counter value reaches zero, the logic block position of the ordered buffer is released.

The method continues at step 264 where the processing entity tags each read operation with a unique ordered tag value. As an example, a first read operation is regarding a first logical data block of the “n” number of logical data blocks of the non-volatile memory and is tagged with a first ordered tag value. The processing entity sends the read operations with their corresponding tags to the non-volatile memory.

The method continues at step 266 where the processing entity receives read responses to the read operations from the non-volatile memory. For example, a first read response is received in response to the first read operation and includes the first ordered tag value.

The method continues at step 268 where the processing entity writes data units contained in the read responses into the ordered buffers in accordance with the ordered tag values. This step will be further described with reference to FIG. 22B. The method continues at step 270 where the processing entity tracks consumption of the data units from the ordered buffers using the counter values.

FIG. 22B expands on the method of FIG. 22A and begins at step 280 where the processing entity compares an order tag value of a current received read response of the read responses with a next expected tag value. The method branches at step 282 based on whether the comparison of step 280 was favorable or not. When the comparison was not favorable, the method continues at step 284 where the processing entity queues the tag of the read response and stores the contents of the logic block in its appropriate place in the ordered buffer, but the contents are not made available for consumption.

When the comparison is favorable, the method continues at step 286 where the processing entity writes the one or more partial data units contained in the current received read response to one of the ordered buffers based on the ordered data tag. The method continues at step 288 where the processing entity increments the next expected tag value. An example of processing the read responses in view of tags and queued tags was provided with reference to FIG. 21C.

FIG. 23 is a schematic block diagram of an example of memory device (MD) buffer queues 1-m being allocated to memory devices 42 of processing core resources 48 of a node of a computing device. Under the control of the database operating system, the main memory 40 of a computing device is divided into a database (DB) memory space 51 and a computing device (CD) memory space 56. The DB memory space 51 is generally and dynamically divided into a DB disk section 53, a DB network section 54, and/or a DB general section 55 as previously discussed. Each of the sections may be further dynamically divided into buffers, queues, or other forms of temporary data storage containers. For the purposes of this figure, dynamically divided means that, in accordance with the DB operating system, a portion of the DB memory space is allocated to a node, a processing core resource (PCR), operation, and/or thread on an as needed basis.

In this example, queues are allocated to the memory devices of the processing core resources (PCR) of a node. As a specific example, the memory device (which includes one or more solid state non-volatile memory devices) of PRC 48-1 is allocated a queue called PCR #1 MD queue 1. The processing module of PCR 48-1 can write data into and read data from PCR #1 MD queue 1. The processing modules 44 of the other processing core resources can read data from PCR #1 MD queue. In an embodiment, processing module 44-m of processing core resource 48-n can write data to the PCR #1 MD queue 1.

As a specific example, the memory device 42-m-1 (which includes one or more solid state non-volatile memory devices) of PRC 48-m is allocated a queue called PCR #m MD queue m. The processing module 44-m of PCR 48-m can write data into and read data from PCR #m MD queue m. The processing modules 44 of the other processing core resources can read data from PCR #m MD queue m. In an embodiment, processing module 44-1 of processing core resource 48-1 can write data to PCR #m MD queue m.

Data is written into and read from the PCR memory device (MD) queues in a format and/or data word size that corresponds to the format and/or data word size of the memory devices. For example, data is stored as pages (i.e., a contiguous block of physical memory) in the memory devices. Accordingly, data is stored in the MD queues in the same sized pages (e.g., 4 Kbytes). By using the same size, the memory interface modules of the processing core resources can directly access the PCR MD queues. In this manner, the queues are pinned memory and improves read and write efficiencies between the memory devices of the processing core resources and main memory by eliminating reads and writes having to be processed by the processing module of the processing core resources. Such processing typically included a format change (e.g., a data size change from one data size to another).

FIG. 24 is a schematic block diagram of an example of a memory device (MD) buffer queue having separate queues 1-z for each memory device of a processing core resource 48 of a node 37 of a computing device 18 and the formatting of the separate queues. This example is a continuation of the example of FIG. 23 , which includes processing core resource 48-1 and PCR #1 MD queue 1. The queue is divided into separate queues for each physical memory device (1-z) of the processing core resource 48-1. Each individual memory device queue (e.g., queue for MD #z) is divided into fields. Each field of a queue includes a pointer (ptr), a logical block address (LBA), and a tag. The pointer points to a physical memory space in the particular memory device (e.g., memory device z) and the LBA is the logical block address for the data of where it is stored in virtual memory space. The tag is a tracking number that corresponds to when an input or output request was made for the data at the LBA.

Entry into a memory device queue is separate and asynchronous from executing an operation regarding the data identified in the field of the queue. For example, when a read request is received for data at LBA xxx, it is tagged with a number, the physical address is determined, and the information is entered into a field of the queue. That completes this process and the operation requesting the read cannot now delete the information from the queue. At some later time, the read request will be processed and the queue cleared.

The physical processing of a read requests is typically not done in the same order as the read requests were received. The read request order, however, is important to ensure that operations flow in a desired order and deadlocks are avoided. The present queue processing allows for out of order read processing while maintain read request ordering. An example of this is provided with reference to FIGS. 25-29A.

FIG. 25 is a schematic block diagram of an example of read requests being received in an order for a memory device of a processing core resource and information regarding the read requests being entered into memory device's queue 270. In this example, 14 read requests have been received in a short time frame (too short to individually process the read request before the next one comes in). Each read request is added to the MD queue. For example, read request 1 is tagged with tag #1, its LBA is added to the LBA portion of the first field, and the pointer to the physical memory is added in its portion of the field. The other read requests are similarly added to the MD queue.

The read requests may be from the same processing core resource, from different processing core resources of the same node, and/or from processing core resources of different nodes of a computing device. As the read requests are entered (i.e., submitted) into the queue, processing of them begins. The processing includes parsing and/or process data memory, return an entry in the queue to the submission side.

FIG. 26 is a schematic block diagram of an example of read requests 272 being processed out of the order in which they were received, the corresponding information in the memory device queue 270 being entered into a ring buffer 274 as the requests are being processed, and positioned in the ring buffer based on tags. In this example, the order in which the read requests are actually processed is shown in the middle table (example processed reads). In this example, read request #3 is the first to be processed and added to a ring buffer in position #3.

The ring buffer is pre-sized to temporarily hold read requests until at least a partial ordered portion of the read requests have been processed. The ring buffer further includes an overflow section 278 to temporarily hold processed read requests that are processed fairly significantly out of the order in which they were requested.

The ring buffer 274 includes a pointer 276 that points to the ring buffer location corresponding to the first read request in the MD queue (e.g., with the tag of #1). In the ring buffer, as long as the first space is empty, a consecutive order of completed read requests. Thus, at this stage of processing read requests, nothing is outputted.

FIG. 27 illustrates the processing of the next five completed read requests. The second processed read request is for the received read request #12. The processed read request is added to position 12 in the ring buffer. The pointer stays pointing a ring #1. The third processed read request is for the received read request #27. Since this read request is significantly out of order for a ring buffer having 12 entries, it is placed in the overflow section. In particular, it is placed in position 13 of the ring buffer.

The fourth processed read request is for the received read request #7. The processed read request is added to position 7 in the ring buffer. The fifth processed read request is for the received read request #4. The processed read request is added to position 4 in the ring buffer. The sixth processed read request is for the received read request 12. The processed read request is added to position 2 in the ring buffer. At this point in time, position 1 is still empty and the pointer continues to point to it.

FIG. 28 illustrates the processing of the next two completed read requests. The seventh processed read request is for the received read request #6. The processed read request is added to position 6 in the ring buffer. The pointer stays pointing a ring #1. The eighth processed read request is for the received read request #1. The processed read request is added to position 1 in the ring buffer. At this point in time, the pointer is now pointing to a non-empty field. With the pointer pointing to a non-empty field, the pointer field and every consecutive field that is not empty has the corresponding read operation completed.

In this example, the first four entries in the ring buffer are not empty. So, the read requests having tag numbers 1-4 are outputted. Once the data is outputted (i.e., read by the requesting entity), the pointer is moved to the next empty location. Position 5 in this example. In addition, positions 1-4 are released and are now at the end of the ring buffer.

FIG. 29A illustrates the processing of the next two completed read requests. The ninth processed read request is for the received read request #8. The processed read request is added to position 9 in the ring buffer. The pointer stays pointing a ring #5. The tenth processed read request is for the received read request #5. The processed read request is added to position 5 in the ring buffer. At this point in time, the pointer is now pointing to a non-empty field. With the pointer pointing to a non-empty field, the pointer field and every consecutive field that is not empty has the corresponding read operation completed.

In this example, the four entries in the ring buffer of 5-8 are not empty. So, the read requests having tag numbers 5-8 are outputted. Once the data is outputted (i.e., read by the requesting entity), the pointer is moved to the next empty location. Position 9 in this example. In addition, positions 5-8 of are released and are now at the end of the ring buffer.

FIG. 29B is a flow diagram illustrating a method for execution by a computing device such as a node 37 within a computing device 18 that implements one or more processing core resources 48, or a computing device 18 that implements one or more nodes 37 each implementing one or more processing core resources 48. In some cases, multiple processing core resources 48, multiple nodes 37, and/or multiple computing devices 18 can each execute some or all of the steps of FIG. 29B in conjunction with execution of their respective operations, for example, as illustrated and discussed in conjunction with FIGS. 23, 24, 25, 26, 27, 28 , and/or 29A. The method of FIG. 29B can include performance of some or all steps illustrated in the examples of FIGS. 25, 26, 27, 28 , and/or 29A by one or more processing core resources, nodes, and/or computing devices. Some or all steps of FIG. 29B can be performed by any processing module of the database system 10.

Step 2902 includes determining, in accordance with a first ordering, a plurality of read requests for a memory device. For example, the memory device is a memory device 42 of FIGS. 23 and/or 24 . For example, the plurality of read requests are received, generated, or otherwise temporally determined one at a time in the first ordering, and/or are otherwise ordered in the first ordering. The plurality of read requests can be implemented via some or all functionality of read requests 272.

Step 2904 includes adding the plurality of read requests to a memory device queue for the memory device in accordance with the first ordering. For example, the memory device queue is implemented as a memory device queue for the memory device stored in main memory 40 as illustrated in FIGS. 23 and/or 24 . The memory device queue can be implemented via some or all features and/or functionality of memory device queue 270. Performing step 2904 to add the plurality of read requests to a memory device queue for the memory device can be based on some or all features and/or functionality illustrated in and/or described in conjunction with FIG. 25 .

Step 2906 includes processing, in accordance with a second ordering that is different from the first ordering, the plurality of read requests in the memory device queue to determine read data for each of the plurality of read requests. For example, the plurality of read requests are temporally processed in the second ordering one at a time by one or more threads of one or more processing core resources. The read data can be determined for each given one of the plurality of read requests based on performing the given read request and/or based on reading corresponding data from a corresponding location as indicated by the given read request. For example, the given read request is processed based on an LBA and/or pointer determined for the read request. Performing step 2904 to process each of the plurality of read requests in the memory device queue to determine read data for each of the plurality of read requests can be based on some or all features and/or functionality illustrated in and/or described in conjunction with FIG. 25 and/or FIG. 26 .

Step 2908 includes adding the read data for the each of the plurality of read requests to one of a set of ordered positions of a ring buffer as the each of the plurality of reads requests is processed. The set of ordered positions of the ring buffer can be based on the first ordering. For example, the ring buffer is implemented via some or all features and/or functionality of ring buffer 274, and/or the set of ordered positions of the ring buffer can be implemented via some or all features and/or functionality of the ring #s of ring buffer 274. The read data can be added as the data of ring buffer 274 at the corresponding ring # of ring buffer 274.

In various embodiments, each of the plurality of reads requests is processed is processed one at a time in the second ordering, and each corresponding read data is added to the of a ring buffer one at a time in the second ordering as each corresponding read request is processed. For example, performing step 2906 to add the read data for the each of the plurality of read requests to one of a set of ordered positions of a ring buffer as the each of the plurality of reads requests is processed can be based on some or all features and/or functionality illustrated in and/or described in conjunction with FIGS. 26, 27, 28 , and/or 29A, such as the addition of data to the ring buffer 274 for some or all of the 1^(st)-10^(th) processed reads illustrated in FIGS. 26-29A.

Step 2910 includes submitting the read data of a subset of the plurality of read requests based on adding the read data for one of the plurality of reads requests to a first ordered position of the set of ordered positions of the ring buffer. The subset of the plurality of read requests can include only consecutively ordered ones of the plurality of read requests having read data in corresponding consecutively ordered positions of the ring buffer, starting from the first ordered position of the set of ordered positions of the ring buffer. For example, the submitting of the read data of a subset of the plurality of read requests can be based on some or all of the outputting of reads, and/or returning of tag #s to the submission side illustrated in and discussed in conjunction with FIGS. 28, 29A and/or 25 . Alternatively or in addition, adding the read data for one of the plurality of reads requests to a first ordered position of the set of ordered positions of the ring buffer can be performed based on some or all of the features and/or functionality of adding the 8^(th) processed read to the ring buffer as illustrated in FIG. 28 and/or of adding the 10^(th) processed read to the ring buffer as illustrated in FIG. 29A.

In various embodiments, the subset of the plurality of read requests is a proper subset of a set of read requests having read data in the ring buffer at a time when the read data for the one of the plurality of reads requests is added to the ring buffer based on the second ordering being different from the first ordering. In various embodiments, the subset of the plurality of read requests included only the first ordered one of the plurality of read requests.

In various embodiments, a set difference between the first ordered one of the plurality of read requests and the subset of the plurality of read requests is non-null. In various embodiments, all read requests included in the set difference between the first ordered one of the plurality of read requests and the subset of the plurality of read requests were processed prior to the first ordered one of the plurality of read requests in accordance with the second ordering.

In various embodiments, a final consecutively ordered one of the subset of the plurality of read requests has one corresponding position in the set of ordered positions of the ring buffer. In various embodiments, another read request not included in the subset of the plurality of read requests has another corresponding position in the set of ordered positions of the ring buffer consecutively after the one corresponding position. In various embodiments, the another read request is not included in the subset of the plurality of read requests based on being processed after the first ordered one of the plurality of read requests.

For example, the subset of the plurality of read requests includes read requests 1, 2, 3, and 4 of the example of FIGS. 25-29A, and this subset is submitted based on adding of read request 1 as the 8^(th) processed read as illustrated in FIG. 28 , where the another read request is implemented as read request 5 of the example of FIGS. 25-29A.

In various embodiments, the method further includes setting a pointer for the ring buffer indicating one of the set of ordered positions corresponding to the first ordered one of the plurality of reads requests of the memory device queue. For example, the pointer is implemented as pointer 276. In various embodiments, the read data of the subset of the plurality of read requests is submitted based on adding the read data to the one of the set of ordered positions indicated by the pointer. For example, the subset is submitted based on: the read data for read request 1 being added to ring #1 in the 8^(th) processed read of FIG. 28 ; and the pointer 276 pointing to the position corresponding to ring #1.

In various embodiments, the method further includes updating the pointer based on submitting the read data of the subset of the plurality of read requests to indicate another position in the set of ordered positions of the ring buffer corresponding to another one of the plurality of reads requests ordered consecutively after a final consecutively ordered one of the subset of the plurality of read requests. For example, the position of the pointer 276 is updated to ring #5 as illustrated in FIG. 28 based on the read data for read requests 1, 2, 3, and 4 being submitted. The method can further include submitting the read data of a second subset of the plurality of read requests based on adding the read data for the another one of the plurality of reads requests to the another position in the set of ordered positions of the ring buffer submitted based on the pointer indicating the another one of the set of ordered positions. The second subset of the plurality of read requests can include only consecutively ordered ones of the plurality of read requests, starting from the another one of the plurality of reads requests in accordance with the first ordering, having read data in corresponding consecutively ordered positions of the ring buffer. For example, the second subset of the plurality of read requests includes read requests 5, 6, 7, and 8 of the example of the example of FIGS. 25-29A, where this second subset is submitted based on read data for read request 5 being added as the 10^(th) processed read, and further based on the pointer 276 pointing to the position for ring #5 at this time.

In various embodiments, adding the plurality of read requests to the memory device queue includes adding an entry for each of the plurality of read requests with a set of field. The set of fields can include: a pointer indicating a physical memory space in the memory device based on the each of the plurality of read requests; a logical block address indicating a virtual memory space based on the each of the plurality of read requests; and/or a tag identifier based on the first ordering. For example, the pointer, logical block address, and/or tag identifier of each read request can be implemented by the pointer, LBA, and tag #, respectively, illustrated in and discussed in conjunction with FIG. 26 .

In various embodiments, adding the read data for the each of the plurality of read requests to the one of the set of ordered positions of the ring buffer includes selecting the one of the set of ordered positions of the ring buffer based on the tag identifier. For example, each given read request has its read data added to a position with a ring # matching the tag # of the given read request as illustrated in FIGS. 26-29A.

In various embodiments, a first proper subset of the set of ordered positions of the ring buffer correspond to a set of consecutively ordered ones of the plurality of read requests, and a second proper subset of the set of ordered positions of the ring buffer correspond to a set of overflow positions. The set of overflow positions can be sequentially after the first proper subset of the set of ordered positions in accordance with the first ordering. For example, the set of overflow positions are implemented as overflow section 278. The method can further include adding the read data for another one of the plurality of read requests to one of the set of overflow positions of the ring buffer based on a number of read requests between the one of the plurality of read requests and the another one of the plurality of read requests in the first ordering being greater than a number of positions between the first ordered one of the set of ordered positions and a last ordered one of the first proper subset of the set of ordered positions. For example, the another one of the plurality of read requests is implemented as read request with tag #27 added as the third processed read as illustrated in FIG. 27 .

In various embodiments, each of the plurality of read requests are requested by a corresponding requesting entity. For example, the corresponding requesting entity of some or all the plurality of read requests is one of a plurality of threads operating on at least one processing core resource, is a processing core resource 48, is a node, and/or is a computing device. In various embodiments, submitting the read data of the subset of the plurality of read requests includes communicating each read data of the subset of the plurality of read requests to the corresponding requesting entity. In various embodiments, the method further includes removing the subset of the plurality of read requests from the memory device queue, for example, based on submitting the subset of the plurality of read requests and/or confirming receipt of the corresponding read data by a corresponding requesting entity.

In various embodiments, the method further includes allocating the memory device queue for the memory device in a first portion of main memory of the computing device, and allocating each of an additional plurality of memory device queues for each one of an additional plurality of memory devices in a plurality of other portions of main memory of the computing device. For example, different memory device queues are allocated for different memory devices via some or all features and/or functionality illustrated in and/or discussed in conjunction with FIGS. 23 and/or 24 . The main memory can be implemented as main memory 40. In some embodiments, the various memory device queues allocated for corresponding memory devices are implemented via portions of memory of DB disk 53 as illustrated in FIG. 23 .

In various embodiments, some or all steps of the method of FIG. 29B is performed for some or all additional plurality of memory device queues for some or all of the additional plurality of memory devices. For example, in various embodiments, the method further includes adding each additional plurality of read requests of a set of additional pluralities of read requests to a corresponding memory device queue of the additional plurality of memory device queues based on an ordering that each additional plurality of read requests is determined. Each read request of the each additional plurality of read requests of the set of additional pluralities of read requests can be added to the corresponding memory device queue based on the each read request corresponding to a request to read data from a corresponding memory device for which the each of the additional plurality of memory device queues is allocated. The method can further include processing each additional plurality of read requests in each corresponding memory device queue in accordance with a different ordering from which they were determined to generate read data for each read request in the each additional plurality of read requests. The method can further include adding the read data for the each read request of the each additional plurality of read requests of the set of additional pluralities of read requests to one of a set of ordered positions of a corresponding ring buffer of a set of additional ring buffers as the each read request of the additional plurality of reads requests is processed in the different ordering. The set of ordered positions of the corresponding ring buffer can be based on the order in which the each additional plurality of read requests were determined. The method can further include submitting the read data of a corresponding subset of one additional plurality of read requests of the set of additional pluralities of read requests based on adding the read data for one of the one additional plurality of reads requests corresponding to a first ordered one of the one additional plurality of read requests to a first ordered position of the set of ordered positions of the corresponding ring buffer. The corresponding subset of the one additional plurality of read requests can include only consecutively ordered ones of the additional plurality of read requests having read data in corresponding consecutively ordered positions of the corresponding ring buffer, starting from the first ordered position of the set of ordered positions of the corresponding ring buffer.

In various embodiments the additional plurality of memory devices includes a first set of memory devices of a first processing core resource, and further includes a second set of memory devices of a second processing core resource. The additional plurality of memory device queues can include a first set of memory device queues for the first set of memory devices, and can further include a second set of memory device queues for the second set of memory devices. For example, the first set of memory device queues can include multiple memory device queues corresponding to multiple memory devices in the first set of memory devices of the first processing core resource, and/or the second set of memory device queues can include multiple memory device queues corresponding to multiple memory devices in the second set of memory devices of the second processing core resource utilizing some or all features and/or functionality illustrated in and/or discussed in conjunction with FIG. 24 .

In various embodiments, a first processing core resource of the computing device implements the memory device, and a second processing core resource of the computing device implements a second memory device. In various embodiments the one additional plurality of read requests are added to a corresponding additional memory device queue for the second memory device, where the one additional plurality of read requests includes at least one read request from the first processing core resource. In various embodiments, the plurality of read requests added to the memory device queue for the memory device resource includes at least one read request from the second processing core resource.

In various embodiments, read data is read from data stored in the memory device, wherein the data stored in the memory device is in accordance with a data format having a fixed size, and/or where entries of the memory device queue are stored in accordance with the data format having the fixed size. For example, the data format is a page, and/or the fixed size is four Kilobytes.

In various embodiments, a computing device, such as a computing device 18 of FIG. 23 or another computing device 18 discussed herein, includes at least one processor, and a memory that stores operational instructions. The operational instructions, when executed by the at least one processor, can cause the computing device to perform some or all steps of FIG. 29B and/or some or all functionality described above in conjunction with the method of FIG. 29B. For example, the operational instructions, when executed by the at least one processor, can cause the computing device to: determine, in accordance with a first ordering, a plurality of read requests for a memory device of the computing device; add the plurality of read requests to a memory device queue for the memory device in accordance with the first ordering; process, in accordance with a second ordering that is different from the first ordering, the plurality of read requests in the memory device queue to determine read data for each of the plurality of read requests; add the read data for the each of the plurality of read requests to one of a set of ordered positions of a ring buffer as the each of the plurality of reads requests is processed, where the set of ordered positions of the ring buffer are based on the first ordering; and/or submit the read data of a subset of the plurality of read requests based on adding the read data for one of the plurality of reads requests corresponding to a first ordered one of the plurality of read requests of the first ordering to a first ordered position of the set of ordered positions of the ring buffer, where the subset of the plurality of read requests includes only consecutively ordered ones of the plurality of read requests having read data in corresponding consecutively ordered positions of the ring buffer, starting from the first ordered position of the set of ordered positions of the ring buffer.

In various embodiments, a non-transitory computer readable storage medium includes at least one memory section that stores operational instructions. The operational instructions, when executed by a processing module that includes a processor and a memory, can cause the processing module to perform some or all steps of FIG. 29B and/or some or all functionality described above in conjunction with the method of FIG. 29B. For example, the operational instructions, when executed by a processing module that includes a processor and a memory, can cause the processing module to determine, in accordance with a first ordering, a plurality of read requests for a memory device; add the plurality of read requests to a memory device queue for the memory device in accordance with the first ordering; process, in accordance with a second ordering that is different from the first ordering, the plurality of read requests in the memory device queue to determine read data for each of the plurality of read requests; add the read data for the each of the plurality of read requests to one of a set of ordered positions of a ring buffer as the each of the plurality of reads requests is processed, wherein the set of ordered positions of the ring buffer are based on the first ordering; and/or submit the read data of a subset of the plurality of read requests based on adding the read data for one of the plurality of reads requests corresponding to a first ordered one of the plurality of read requests of the first ordering to a first ordered position of the set of ordered positions of the ring buffer, wherein the subset of the plurality of read requests includes only consecutively ordered ones of the plurality of read requests having read data in corresponding consecutively ordered positions of the ring buffer, starting from the first ordered position of the set of ordered positions of the ring buffer.

FIG. 30 is a schematic block diagram of an example of direct memory access for a processing core resource 48 and/or for a network connection 41 as previously discussed. Within a computing device, the main memory 40 is logically partitioned into a database section (e.g., database memory space 51) and a computing device section (e.g., CD memory space 56 as previously discussed). In an embodiment, the main memory 40 is logically shared among the processing cores of the nodes of a computing device under the control of the database operating system. In another embodiment, the main memory 40 is further logically divided by the database operating system such that a processing core resource of a node of the computing device is allocated its own main memory.

The database memory space 51 is logically and dynamically divided into a database operating system (DB OS) 52 section, a DB disk section 53, a DB network 54 section, and a DB general 55 section. The database operating system determines the size of the disk section, the network section, and the general section based on memory requirements for various operations being performed by the processing core resources, the nodes, and/or the computing device. As such, as the processing changes within a computing device, the size of the disk section, the network section, and the general section will most likely vary based on memory requirements for the changing processing.

Within the computing device, data stored on the memory devices is done in accordance with a data block format (e.g., 4 K byte block size). As such, data written to and read from the memory devices via the disk section of the main memory is done so in 4 K byte portions (e.g., one or more 4 K byte blocks). Conversely, network messages use a different format and are typically of a different size (e.g., 1 M byte messages).

To facilitate lock free and efficient data transfers, the disk section of the main memory is formatted in accordance with the data formatting of the memory devices (e.g., 4 K byte data blocks) and the network section of the main memory is formatted in accordance with network messaging formats (e.g., 1 M byte messages). Thus, when the processing module 44 is processing disk access requests, it uses the DB disk section 53 of the main memory 40 in a format corresponding to the memory device 42. Similarly, when the processing module 44 is processing network communication requests, it uses the DB network 54 section of the main memory 40 in a format corresponding to network messaging format(s).

In this manner, accessing memory devices is a separate and independent function of processing network communication requests. As such, the memory interface module 43 can directly access the DB disk 53 section of the main memory 40 with little to no intervention of the processing module 44. Similarly, the network interface module 46 can directly access the DB network section 54 of the main memory 40 with little to no intervention of the processing module 44. This substantially reduces interrupts of the processing module 44 to process network communication requests and memory device access requests. This also allows for lock free operation of memory device access requests and network communication requests with increased parallel operation of such requests.

FIGS. 31-32 are schematic block diagrams of an example of processing received data and distributing the processed table for storage in the database system when a computing device 18 in a storage cluster 1 is unavailable. When this occurs, the host computing device 18 (e.g., L2 computing device of a storage cluster or L1 computing device) reorganizes a segment group or creates a different type of a segment group. In either case, the resulting segment group (assuming 5 segments in the group) has four segments that include data and a fifth segment that only includes parity data.

FIG. 32 illustrates the host computing device 18 sending, via local communications 26, the four data segments to the four active computing devices 18 in the cluster 35 and holds the parity segment for the unavailable computing device. When the unavailable computing device becomes available, the host computing device sends it the parity segment.

FIG. 33 is a schematic block diagram of an example of using allocated memory of main memory 40 for manifest data and/or index data of a data segment associated with a processing core resource. Data segments, such as the data segment depicted on FIG. 33 are the fundamental building block for data storage, where the segment (in this example 32 GB) is divided into coding blocks of, for example 4 KB. Each data segment includes a data & parity section 280, a manifest (or metadata) section 282, and multiple index sections 0 through x, along with a statistics section 284 where appropriate.

Main memory 40, as discussed previously, can be random access memory (RAM) or any other suitable cache memory structure, is associated with each node, or can alternatively be associated with a plurality of nodes and is shown as an allocated memory resource. Specifically, the main memory 40 may be allocated to provide defined space for the example elements of a database system, including memory space allocated for data 286, memory space allocated for metadata 288, and memory space allocated for keys 290.

When the main memory 40 is not large enough to store all the metadata and key data for the associated data and parity of a data segment the metadata allocation and key data allocation in main memory can be used to point to the location of the data (along with the data ordering methodology) in a given data segment. The allocated memory illustrated for manifest data and/or index data of a data segment can be incorporated at a processing core resource, as shown, and/or at a computing device level and/or node level.

FIG. 34 provides a schematic block diagram of an example of a partition allocator 296 allocating partitions of the allocated memory of main memory to requesting operations (e.g., requests 300). Operations running on processing cores and or nodes (shown as requesting op 1 through requesting op y) execute the requests 300 over the network to one or computing devices associated with the database system. The computing devices include one more modules adapted as a partition allocator for the database memory, in order to process the requests in an ordered fashion. The partition allocator 296 is further adapted to create a queue 302 for the requests. The example shown illustrates a FIFO partition request queue 298; other alternatives include any queue that can be used to order the execution of requests from requesting entities.

Once the queue is created database memory space is allocated for the metadata 288 and/or keys 290 as discussed with regard to FIG. 33 above. In the example shown the database memory is divided into a plurality of pages (shown as pages 0 through page n). In an example there are a variable number of partitions defined for each page. For example, a page could be defined as a 1 gigabyte (GB) memory space with a partition size of 256-megabyte (MB) to render four (4) partitions per page. In an example page size can be selectable within any practical limit, and the number of partitions in each page can be selectable in a like manner.

FIG. 35 is a logic diagram of an example of a method of allocating partitions of the allocated memory of main memory to requesting operations. In an example, the partition allocator of FIG. 34 receives, at step 310, partition allocation requests based on operations running on processing cores and or nodes. The requests can be in response to a query initiated by the computing device receiving the request, or they may be initiated based on the operations themselves. Each operation responsible for a request will know how many partitions will be required based on the size of the metadata and/or keys it is retrieving from the database. Considering a single request received at the computing device, once the request is received at a next step the computing device determines whether enough partitions are available. At step 312, the computing device can determine whether the partitions are available based on prior knowledge and/or based on whether any requests are currently held in a partition queue, such as a FIFO queue. For example, if a FIFO queue has been created and already includes a previous request the computing device will determine that sufficient partitions are not available to service the request. In this case, at step 314, the request is queued in the FIFO queue in a step where the request is cycled through to the previous step 312.

If enough partitions are available the computing device allocates partitions at step 316, and at the next step 318, determines whether a partition has already been loaded with the desired content, where the content is the metadata for an associated data segment and/or a portion of the key column(s) for the associated data segment. If a partition has not already been loaded with the desired content the metadata and/or key column(s) are loaded into the identified partitions at next step 320. At step 322 the computing device determines whether the operation is done executing with the allocated partitions, and when it is, at step 326, the computing device releases the allocated partitions for use by another operation. When the operation is not executed with the allocated partitions, at step 324, the computing device ensures that the allocated partitions are maintained until the operation is executed or times out. Each operation requesting a partition is required to guarantee that the associated request can be either executed or that progress can be made toward execution so that the partition will not be deadlocked.

Additionally, a duty cycle can be established whereby on a regular interval each operation with one or more partitions that have been allocated are released and the operation associated with the request will initiate new partition requests for the same content. In such a case already allocated data can remain in main memory. The duty cycle can be based on a “deadlock avoidance” contract that all operations follow in order to ensure that nonperforming operations release allocated partitions on a regular interval in order to avoid locking up memory partitions and thereby decreasing performance of database operations.

When a partition has already been loaded with the desired content the method continues at step 328, where the computing device retains the partition(s) for already loaded content and the content is used for execution by the associated requestor(s). At step 330, the computing device determines whether the operation that initiated the partition allocation has been executed and when the operation has been executed the computing device releases the allocated partitions in main memory at step 332, as long as the partitions are not shared with another request and/or operation. When the computing device determines that the operation has not completed execution associated with the underlying request the computing device retains the allocated partition until the execution is complete by looping back to step 328.

FIG. 36 is a schematic block diagram of another example of a partition allocator allocating partitions of the allocated memory of main memory to requesting operations. In an example at time t0 a single partition is reserved by an operation (op 0) for particular content, in this case metadata X. At time t1 metadata X has been loaded in main memory for the requesting operation. At time t2 another operation (op 1) requests two (2) partitions to be allocated for each of metadata X, which has already been loaded and metadata Y. At time t3 op 0 and op 1 share the already loaded metadata X and metadata Y is loaded (metadata X is not loaded again, since it has already been loaded) and the reservation for op 1 request for metadata X is maintained.

At time t4 op 0 has completed execution of the operation for which metadata x was loaded and releases the allocated partition for metadata X, but metadata X is not released, because op 1 may still be using it. At time t5 both op 0 and op 1 are complete, so the partition reserved by op 1 for X is released.

It is noted that terminologies as may be used herein such as bit stream, stream, signal sequence, etc. (or their equivalents) have been used interchangeably to describe digital information whose content corresponds to any of a number of desired types (e.g., data, video, speech, text, graphics, audio, etc. any of which may generally be referred to as ‘data’).

As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. For some industries, an industry-accepted tolerance is less than one percent and, for other industries, the industry-accepted tolerance is 10 percent or more. Other examples of industry-accepted tolerance range from less than one percent to fifty percent. Industry-accepted tolerances correspond to, but are not limited to, component values, integrated circuit process variations, temperature variations, rise and fall times, thermal noise, dimensions, signaling errors, dropped packets, temperatures, pressures, material compositions, and/or performance metrics. Within an industry, tolerance variances of accepted tolerances may be more or less than a percentage level (e.g., dimension tolerance of less than +/−1%). Some relativity between items may range from a difference of less than a percentage level to a few percent. Other relativity between items may range from a difference of a few percent to magnitude of differences.

As may also be used herein, the term(s) “configured to”, “operably coupled to”, “coupled to”, and/or “coupling” includes direct coupling between items and/or indirect coupling between items via an intervening item (e.g., an item includes, but is not limited to, a component, an element, a circuit, and/or a module) where, for an example of indirect coupling, the intervening item does not modify the information of a signal but may adjust its current level, voltage level, and/or power level. As may further be used herein, inferred coupling (i.e., where one element is coupled to another element by inference) includes direct and indirect coupling between two items in the same manner as “coupled to”.

As may even further be used herein, the term “configured to”, “operable to”, “coupled to”, or “operably coupled to” indicates that an item includes one or more of power connections, input(s), output(s), etc., to perform, when activated, one or more its corresponding functions and may further include inferred coupling to one or more other items. As may still further be used herein, the term “associated with”, includes direct and/or indirect coupling of separate items and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that a comparison between two or more items, signals, etc., provides a desired relationship. For example, when the desired relationship is that signal 1 has a greater magnitude than signal 2, a favorable comparison may be achieved when the magnitude of signal 1 is greater than that of signal 2 or when the magnitude of signal 2 is less than that of signal 1. As may be used herein, the term “compares unfavorably”, indicates that a comparison between two or more items, signals, etc., fails to provide the desired relationship.

As may be used herein, one or more claims may include, in a specific form of this generic form, the phrase “at least one of a, b, and c” or of this generic form “at least one of a, b, or c”, with more or less elements than “a”, “b”, and “c”. In either phrasing, the phrases are to be interpreted identically. In particular, “at least one of a, b, and c” is equivalent to “at least one of a, b, or c” and shall mean a, b, and/or c. As an example, it means: “a” only, “b” only, “c” only, “a” and “b”, “a” and “c”, “b” and “c”, and/or “a”, “b”, and “c”.

As may also be used herein, the terms “processing module”, “processing circuit”, “processor”, “processing circuitry”, and/or “processing unit” may be a single processing device or a plurality of processing devices. Such a processing device may be a microprocessor, micro-controller, digital signal processor, microcomputer, central processing unit, field programmable gate array, programmable logic device, state machine, logic circuitry, analog circuitry, digital circuitry, and/or any device that manipulates signals (analog and/or digital) based on hard coding of the circuitry and/or operational instructions. The processing module, module, processing circuit, processing circuitry, and/or processing unit may be, or further include, memory and/or an integrated memory element, which may be a single memory device, a plurality of memory devices, and/or embedded circuitry of another processing module, module, processing circuit, processing circuitry, and/or processing unit. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any device that stores digital information. Note that if the processing module, module, processing circuit, processing circuitry, and/or processing unit includes more than one processing device, the processing devices may be centrally located (e.g., directly coupled together via a wired and/or wireless bus structure) or may be distributedly located (e.g., cloud computing via indirect coupling via a local area network and/or a wide area network). Further note that if the processing module, module, processing circuit, processing circuitry and/or processing unit implements one or more of its functions via a state machine, analog circuitry, digital circuitry, and/or logic circuitry, the memory and/or memory element storing the corresponding operational instructions may be embedded within, or external to, the circuitry comprising the state machine, analog circuitry, digital circuitry, and/or logic circuitry. Still further note that, the memory element may store, and the processing module, module, processing circuit, processing circuitry and/or processing unit executes, hard coded and/or operational instructions corresponding to at least some of the steps and/or functions illustrated in one or more of the Figures. Such a memory device or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of method steps illustrating the performance of specified functions and relationships thereof. The boundaries and sequence of these functional building blocks and method steps have been arbitrarily defined herein for convenience of description. Alternate boundaries and sequences can be defined so long as the specified functions and relationships are appropriately performed. Any such alternate boundaries or sequences are thus within the scope and spirit of the claims. Further, the boundaries of these functional building blocks have been arbitrarily defined for convenience of description. Alternate boundaries could be defined as long as the certain significant functions are appropriately performed. Similarly, flow diagram blocks may also have been arbitrarily defined herein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence could have been defined otherwise and still perform the certain significant functionality. Such alternate definitions of both functional building blocks and flow diagram blocks and sequences are thus within the scope and spirit of the claims. One of average skill in the art will also recognize that the functional building blocks, and other illustrative blocks, modules and components herein, can be implemented as illustrated or by discrete components, application specific integrated circuits, processors executing appropriate software and the like or any combination thereof.

In addition, a flow diagram may include a “start” and/or “continue” indication. The “start” and “continue” indications reflect that the steps presented can optionally be incorporated in or otherwise used in conjunction with one or more other routines. In addition, a flow diagram may include an “end” and/or “continue” indication. The “end” and/or “continue” indications reflect that the steps presented can end as described and shown or optionally be incorporated in or otherwise used in conjunction with one or more other routines. In this context, “start” indicates the beginning of the first step presented and may be preceded by other activities not specifically shown. Further, the “continue” indication reflects that the steps presented may be performed multiple times and/or may be succeeded by other activities not specifically shown. Further, while a flow diagram indicates a particular ordering of steps, other orderings are likewise possible provided that the principles of causality are maintained.

The one or more embodiments are used herein to illustrate one or more aspects, one or more features, one or more concepts, and/or one or more examples. A physical embodiment of an apparatus, an article of manufacture, a machine, and/or of a process may include one or more of the aspects, features, concepts, examples, etc. described with reference to one or more of the embodiments discussed herein. Further, from figure to figure, the embodiments may incorporate the same or similarly named functions, steps, modules, etc. that may use the same or different reference numbers and, as such, the functions, steps, modules, etc. may be the same or similar functions, steps, modules, etc. or different ones.

Unless specifically stated to the contra, signals to, from, and/or between elements in a figure of any of the figures presented herein may be analog or digital, continuous time or discrete time, and single-ended or differential. For instance, if a signal path is shown as a single-ended path, it also represents a differential signal path. Similarly, if a signal path is shown as a differential path, it also represents a single-ended signal path. While one or more particular architectures are described herein, other architectures can likewise be implemented that use one or more data buses not expressly shown, direct connectivity between elements, and/or indirect coupling between other elements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of the embodiments. A module implements one or more functions via a device such as a processor or other processing device or other hardware that may include or operate in association with a memory that stores operational instructions. A module may operate independently and/or in conjunction with software and/or firmware. As also used herein, a module may contain one or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes one or more memory elements. A memory element may be a separate memory device, multiple memory devices, or a set of memory locations within a memory device. Such a memory device may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, a quantum register or other quantum memory and/or any other device that stores data in a non-transitory manner. Furthermore, the memory device may be in a form of a solid-state memory, a hard drive memory or other disk storage, cloud memory, thumb drive, server memory, computing device memory, and/or other non-transitory medium for storing data. The storage of data includes temporary storage (i.e., data is lost when power is removed from the memory element) and/or persistent storage (i.e., data is retained when power is removed from the memory element). As used herein, a transitory medium shall mean one or more of: (a) a wired or wireless medium for the transportation of data as a signal from one computing device to another computing device for temporary storage or persistent storage; (b) a wired or wireless medium for the transportation of data as a signal within a computing device from one element of the computing device to another element of the computing device for temporary storage or persistent storage; (c) a wired or wireless medium for the transportation of data as a signal from one computing device to another computing device for processing the data by the other computing device; and (d) a wired or wireless medium for the transportation of data as a signal within a computing device from one element of the computing device to another element of the computing device for processing the data by the other element of the computing device. As may be used herein, a non-transitory computer readable memory is substantially equivalent to a computer readable memory. A non-transitory computer readable memory can also be referred to as a non-transitory computer readable storage medium.

While particular combinations of various functions and features of the one or more embodiments have been expressly described herein, other combinations of these features and functions are likewise possible. The present disclosure is not limited by the particular examples disclosed herein and expressly incorporates these other combinations. 

What is claimed is:
 1. A method for execution by a computing device, comprising: receiving a plurality of partition allocation requests based on execution of a corresponding plurality of query operations in conjunction with execution of a corresponding query; and processing the plurality of partition allocation requests in conjunction with the execution of the corresponding query, wherein processing a first partition allocation request of the plurality of partition allocation requests corresponding to execution of a first operation of the corresponding plurality of query operations is based on: allocating a set of partitions of a plurality of partitions based on determining a number of required partitions indicated in the first partition allocation request are available, wherein the set of partitions includes the number of required partitions; loading content into the set of partitions for access in executing the first operation based on determining the content is not already loaded into another set of partitions of the plurality of partitions; facilitating access to the content via the set of partitions in conjunction with execution of the first operation; and releasing the set of partitions based on determining the first operation has completed access of the content in conjunction with the execution of the first operation.
 2. The method of claim 1, wherein the first partition allocation request indicates the number of required partitions based at least one: of a size of metadata to be retrieved and stored in the set of partitions; or a size of keys to be retrieved and stored in the set of partitions, wherein the content includes at least one of: the metadata; or the keys.
 3. The method of claim 1, wherein processing a second partition allocation request of the plurality of partition allocation requests corresponding to execution of a second operation of the corresponding plurality of query operations is based on: adding the second partition allocation request to a queue of requests based on determining not enough partitions are available to service the second partition allocation request.
 4. The method of claim 3, wherein determining not enough partitions are available to service the second partition allocation request is based on determining the queue of requests includes the first partition allocation request based on the first partition allocation request being received prior to the second partition allocation request, wherein processing the second partition allocation request is further based on: allocating a second set of partitions of the plurality of partitions for the second partition allocation request after releasing the set of partitions, wherein the second set of partitions and the set of partitions have a non-null intersection.
 5. The method of claim 1, wherein, after loading the content into the set of partitions in conjunction with processing the first partition allocation request for the first operation, a second partition allocation request of the plurality of partition allocation requests corresponding to execution of a second operation of the corresponding plurality of query operations is processed based on: allocating a second set of partitions of the plurality of partitions based on the second partition allocation request indicating second content for access in executing the second operation; determining at least some of the second content indicated in the second partition allocation request is already loaded in a subset of the set of partitions for the first operation based on processing the first partition allocation request; loading only remaining content of the second content not already loaded in any of the plurality of partitions into a proper subset of the second set of partitions based on determining the at least some of the second content is already loaded; and facilitating access to the second content via the subset of the set of partitions and the proper subset of the second set of partitions in conjunction with execution of the second operation.
 6. The method of claim 5, wherein processing the second partition allocation request is further based on: retaining allocation of all of the second set of partitions during execution of the second operation; and releasing the second set of partitions based on determining the second operation has completed access of the second content in conjunction with the execution of the second operation.
 7. The method of claim 6, wherein a set difference between the second set of partitions and the proper subset of the second set of partitions remains unloaded while allocated during execution of the second operation based on the at least some of the second content being already loaded in at least one of the set of partitions.
 8. The method of claim 5, wherein the first operation is executed during a first temporal period, wherein the second operation is executed during a second temporal period overlapping with the first temporal period and ending after the first temporal period, and wherein the subset of the set of partitions are retained after completing execution of the first operation for a remainder of the second temporal period based on the second content accessed in conjunction executing the second operation being loaded in the subset of the set of partitions.
 9. The method of claim 8, wherein the subset of the set of partitions is a proper subset of the set of partitions, wherein a set difference between the set of partitions and the subset of the set of partitions is released at a first time corresponding to completion of the first operation, wherein the subset of the set of partitions are released at a second time corresponding to completion of the second operation, and wherein the second time is after the first time.
 10. The method of claim 1, wherein each of the plurality of partition allocation requests are generated based on a guarantee that: a corresponding operation of the corresponding plurality of query operations can be executed; or that progress can be made in executing the corresponding query.
 11. The method of claim 1, wherein the plurality of partition allocation requests are processed based on implementing a duty cycle by releasing partitions, allocated for ones of plurality of partition allocation requests corresponding to ones of the corresponding plurality of query operations that are nonperforming operations for a threshold amount of time, on a regular interval associated with the threshold amount of time based on adhering to a deadlock avoidance contract.
 12. The method of claim 11, wherein processing a second partition allocation request of the plurality of partition allocation requests corresponding to execution of a second operation of the corresponding plurality of query operations is based on: allocating, at a first time, a second set of partitions of the plurality of partitions based on the second partition allocation request indicating second content for access in executing the second operation; loading the second content into the second set of partitions; and releasing, at a second time after the first time, the second set of partitions prior to facilitating access to the content via the set of partitions in conjunction with execution of the second operation based on the regular interval elapsing at the second time, wherein the second operation is a nonperforming operation during a temporal period from the first time to the second time based on the second operation not executing during the temporal period.
 13. The method of claim 12, further comprising, after the second time: receiving a new partition allocation request corresponding to execution of the second operation indicating the second content; allocating, at a third time after the second time, another second set of partitions of the plurality of partitions based on the new partition allocation request indicating the second content for access in executing the second operation; loading the second content into the another second set of partitions; facilitating access to the content via the another second set of partitions in conjunction with execution of the second operation prior to elapsing of the regular interval after the third time; and releasing the another second set of partitions prior to the elapsing of the regular interval after the third time based on determining the second operation has completed access of the content in conjunction with the execution of the second operation prior to the elapsing of the regular interval after the third time.
 14. A computing device includes: at least one processor; and a memory that stores operational instructions that, when executed by the at least one processor, cause the computing device to: receive a plurality of partition allocation requests based on execution of a corresponding plurality of query operations in conjunction with execution of a corresponding query; and process the plurality of partition allocation requests in conjunction with the execution of the corresponding query, wherein processing a first partition allocation request of the plurality of partition allocation requests corresponding to execution of a first operation of the corresponding plurality of query operations is based on: allocating a set of partitions of a plurality of partitions based on determining a number of required partitions indicated in the first partition allocation request are available, wherein the set of partitions includes the number of required partitions; loading content into the set of partitions for access in executing the first operation based on determining the content is not already loaded into another set of partitions of the plurality of partitions; facilitating access to the content via the set of partitions in conjunction with execution of the first operation; and releasing the set of partitions based on determining the first operation has completed access of the content in conjunction with the execution of the first operation.
 15. The computing device of claim 14, wherein the first partition allocation request indicates the number of required partitions based at least one: of a size of metadata to be retrieved and stored in the set of partitions; or a size of keys to be retrieved and stored in the set of partitions, wherein the content includes at least one of: the metadata; or the keys.
 16. The computing device of claim 14, wherein processing a second partition allocation request of the plurality of partition allocation requests corresponding to execution of a second operation of the corresponding plurality of query operations is based on: adding the second partition allocation request to a queue of requests based on determining not enough partitions are available to service the second partition allocation request.
 17. The computing device of claim 14, wherein, after loading the content into the set of partitions in conjunction with processing the first partition allocation request for the first operation, a second partition allocation request of the plurality of partition allocation requests corresponding to execution of a second operation of the corresponding plurality of query operations is processed based on: allocating a second set of partitions of the plurality of partitions based on the second partition allocation request indicating second content for access in executing the second operation; determining at least some of the second content indicated in the second partition allocation request is already loaded in a subset of the set of partitions for the first operation based on processing the first partition allocation request; loading only remaining content of the second content not already loaded in any of the plurality of partitions into a proper subset of the second set of partitions based on determining the at least some of the second content is already loaded; and facilitating access to the second content via the subset of the set of partitions and the proper subset of the second set of partitions in conjunction with execution of the second operation.
 18. The computing device of claim 17, wherein the first operation is executed during a first temporal period, wherein the second operation is executed during a second temporal period overlapping with the first temporal period and ending after the first temporal period, and wherein the subset of the set of partitions are retained after completing execution of the first operation for a remainder of the second temporal period based on the second content accessed in conjunction executing the second operation being loaded in the subset of the set of partitions.
 19. The computing device of claim 14, wherein the plurality of partition allocation requests are processed based on implementing a duty cycle by releasing partitions, allocated for ones of plurality of partition allocation requests corresponding to ones of the corresponding plurality of query operations that are nonperforming operations for a threshold amount of time, on a regular interval associated with the threshold amount of time based on adhering to a deadlock avoidance contract.
 20. A non-transitory computer readable storage medium comprises: at least one memory section that stores operational instructions that, when executed by a processing module that includes a processor and a memory, causes the processing module to: receive a plurality of partition allocation requests based on execution of a corresponding plurality of query operations in conjunction with execution of a corresponding query; and process the plurality of partition allocation requests in conjunction with the execution of the corresponding query, wherein processing a first partition allocation request of the plurality of partition allocation requests corresponding to execution of a first operation of the corresponding plurality of query operations is based on: allocating a set of partitions of a plurality of partitions based on determining a number of required partitions indicated in the first partition allocation request are available, wherein the set of partitions includes the number of required partitions; loading content into the set of partitions for access in executing the first operation based on determining the content is not already loaded into another set of partitions of the plurality of partitions; facilitating access to the content via the set of partitions in conjunction with execution of the first operation; and releasing the set of partitions based on determining the first operation has completed access of the content in conjunction with the execution of the first operation. 